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Look for: Understanding of effective data visualization techniques. What to Expect: Discussion on using appropriate chart types, maintaining visual consistency, avoiding clutter, and focusing on clear and actionable insights.

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Power BI is an amalgamation of these major components: - Power Query (for data mash-up and transformation): You can use this to extract data from various databases (like SQL Server, MySql, and many others ) and to delete a chunk of data from various sources. - Power Pivot (for tabular data modeling): It is a data modeling engine that uses a functional language called Data Analysis Expression (DAX) to perform the calculations. Also, creates a relationship between various tables to be viewed as pivot tables. - Power View (for viewing data visualizations): The view provides an interactive display of various data sources to extract metadata for proper data analysis. - Power BI Desktop (a companion development tool): Power Desktop is an aggregated tool of Power Query, Power View, and Power Pivot. Create advanced queries, models, and reports using the desktop tool. - Power BI Mobile (for Android, iOS, Windows phones): It gives an interactive display of the dashboards from the site onto these OS, effortlessly. - Power Map (3D geo-spatial data visualization). - Power Q&A (for natural language Q&A).

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Yes, I've worked on: BRD (Business Requirement Document): Captures project requirements. Closure Docs: Summarizes project completion. New Release Docs: Documents feature updates. Testing Docs: Details test cases and results.

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Power BI can connect to many different types of data sources, making it incredibly flexible. The main categories include: - Files and spreadsheets: Commonly used sources like Excel files, CSV files, or other document formats that businesses frequently rely on for day-to-day operations. - Databases and cloud services: Includes popular databases like SQL Server, Azure SQL, or Oracle, as well as cloud services like Azure Analysis Services or cloud-based datasets. - Content packs and online services: These include pre-built data packs shared by service providers (like Salesforce or Google Analytics) or content shared by colleagues within your organization, making setup fast and straightforward. - Web and online data: Power BI also connects directly to web-based sources, letting you analyze and visualize data from APIs, social media, or web analytics platforms.

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Three fundamental concepts of DAX are: Syntax: Syntax is the formula which includes the functions. If a Syntax is incorrect, it will result in an error. Functions: Functions are arguments with specific orders to perform. It helps to calculate any particular order as required. Context: Context are of two types: Row Context and Filter Context. Row Context is used when a formula has a Function that applies a filter to identify a row in a table. Filter Context is used when one or more filters are used to get a value.

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I rely on line charts, scatter plots, and conditional formatting. I also use Z-score DAX logic to detect outliers. The “Analyze” feature helps explain changes in values quickly.

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Candidate NPS went from 32 to 78 after implementing AIR, as candidates love the flexibility of interviewing on their own schedule and the AI adapts to each person naturally.

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Filter context is a fundamental concept in Power BI that determines the data scope on which DAX formulas operate. It influences how measures calculate and return results in visualizations and reports, ensuring that calculations are relevant to the data being analyzed. For example When a measure is calculated in Power BI, it considers any filters that have been applied from slicers, visualizations, pages, and DAX formulas. Properly understanding filter context ensures accurate and relevant calculations, and is critical for reliable reports and insights.

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The following are the reasons for low performance

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Use a star schema with dimension and fact tables. Avoid bi-directional relationships unless needed. Rename columns clearly. Reduce cardinality when possible. Always hide unnecessary columns from the report view.

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Power BI is a business intelligence and Analytics tool for non-technical and technical users to manage, analyze, visualize and share data with others. One of its key features is visualization – that is, presenting data and insights using appealing visuals. Among the visuals available in power BI are maps.

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Assume Referential Integrity is a feature to increase query performance for joins when data includes referential integrity. This feature is enabled from the data menu. It will add a joined table in the query if data has referential integrity.

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There are two types of data roles in Tableau – discrete and continuous dimension. Discrete data roles are values that are counted as distinct and separate and can only take individual values within a range. Examples: number of threads in a sheet, customer name or row ID or State. Discrete values are shown as blue pills on the shelves and blue icons in the data window. Continuous data roles are used to measure continuous data and can take on any value within a finite or infinite interval. Examples: unit price, time and profit or order quantity. Continuous variables behave in a similar way in that they can take on any value. Continuous values are shown as green pills.

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C) DAX

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In my previous projects, I used DAX for calculations like running totals, year-over-year growth, and dynamic segmentation. A particularly challenging measure was calculating a moving average for sales over a 12-month period while excluding weekends and holidays. I implemented this using a combination of CALCULATE, FILTER, and DATESBETWEEN functions, along with a custom date table that marked working days. The formula was: Moving Avg = CALCULATE( AVERAGE(Sales[Amount]), FILTER( ALL('Date'), 'Date'[Date] > MAX('Date'[Date]) - 365 && 'Date'[IsWorkingDay] = TRUE ) )

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Global filters can be applied to sheets, stories, and dashboards.

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The primary elements of Power BI consist of: - Power Query is an engine for data mashups and transformations. - Power Pivot: An engine for data modelling and computation. - One tool for data visualisation is Power View. - A 3D tool for visualising geographic data is called Power Map. - A cloud-based platform called Power BI Service allows users to collaborate and share reports and dashboards. - Tabular Editor: A sophisticated tool for working with tabular models that is utilised with Analysis Services and Power BI. It is especially helpful for improving and optimising data models in SQL Server Analysis Services (SSAS) and Power BI. - Power BI Premium: An all-inclusive, cutting-edge cloud-based analytics service with more tools for business intelligence and large-scale data modelling, improved performance, and dedicated cloud resources.

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I created a 'data quality' dashboard comparing yesterday's row counts, null percentages, and key metrics vs. 7-day averages. If variance exceeds thresholds, Slack notifies the data team. That catches ETL failures before end users notice.

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Power BI uses two main languages: M-Language: - Purpose: Used for data transformation in Power Query Editor. - Functionality: Helps clean, reshape, and prepare data before it's loaded into the data model. DAX (Data Analysis Expressions): - Purpose: Used for data analysis and creating calculations. - Functionality: Allows you to create measures, calculated columns, and complex aggregations to analyze data. ? Power BI uses M-Language for data transformation and DAX for data analysis and calculations.

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Parameters in Tableau allow users to dynamically change values in calculations, filters, and reference lines. For instance, I created a parameter to let users select different time periods, which updated the sales trend analysis in real-time, providing a flexible and interactive user experience.

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In Power BI, data storage depends on the connectivity mode you choose. Import Mode: - Data is imported into Power BI and stored within the Power BI memory cache dataset itself. - Best for smaller datasets or when fast performance is needed, as the data is stored in-memory. DirectQuery Mode: - Data remains in the source system, and Power BI queries it in real-time. - Ideal for large datasets or when you need the most current data. Performance can be slower since queries are sent to the original data source. Composite Models: - Allow a report to have two or more data connections, including DirectQuery connections or Import, in any combination. - You can set the storage mode for each table individually in your model. - You can choose between Import, DirectQuery, and Dual. - Dual Mode combines both Import and DirectQuery modes for a single table. The mode used depends on the context: - Calculations or measures requiring real-time data will trigger DirectQuery mode. - Calculations that can be performed on pre-cached data will use Import mode. - Dual Mode combines both Import and DirectQuery modes for a single table. The mode used depends on the context: ? In Power BI, data storage depends on the connectivity mode: Import Mode for in-memory storage, DirectQuery Mode for real-time queries, and Composite Models for a mix of both.

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It identifies factors that influence a metric, helping to understand what drives changes in the data.

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The data can be refreshed in the Gateway in PowerBI by scheduling refresh.

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Create a group by right clicking on a field in data pane and select create -> group and select the fields to be grouped the general tab and define the condition for grouping in conditions tab. Then right click on this group and select create -> set and then right click on the set or any empty place in the data pane and select create calculated field then you can use this group as a set in this calculated field.

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Cleaning and preparing data is a crucial step in the data analysis process, as it ensures that your visualizations are accurate and meaningful. In my experience, there are several key steps I take when cleaning and preparing data for analysis in Tableau: 1. Assessing data quality: Before diving into the data, I like to take a step back and assess the overall quality of the data set. This involves looking for inconsistencies, errors, or missing values that may impact the analysis. 2. Removing unnecessary columns: It's important to only include relevant data in your analysis. I usually start by identifying and removing any columns that are not needed for the specific analysis or visualization I'm working on. 3. Handling missing or null values: Missing or null values can cause issues in your analysis, so it's important to address them. Depending on the situation, I might choose to either fill in the missing values with a default value or remove the rows containing missing values altogether. 4. Data transformation: Sometimes, data needs to be transformed or manipulated before it can be used in Tableau. This might involve creating calculated fields, pivoting data, or aggregating data at different levels of granularity. 5. Ensuring consistency: To ensure accurate analysis, it's important to make sure that data is consistent across the entire data set. This might involve standardizing units of measurement, formatting dates, or converting text to numerical values. 6. Validating the data: Once the data has been cleaned and prepared, I like to validate the data by cross-checking it with other sources or performing some basic analysis to make sure the results make sense. By following these steps, I can ensure that my data is clean, accurate, and ready for analysis in Tableau.

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The AVG function is used to calculate the average (mean) value of a numeric field within a dataset, it is used to analyze and visualize the central tendency of a dataset. Create a calculated field and in the calculated editor, use the AVG function to calculate the average of a numeric field. AVG([Numeric Field)] We can use the AVG function to display the average value in charts, graphs or tables to understand the central tendency of a dataset or we can use it to compare the average values across different categories or time periods to identify trends or anomalies.

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When a VP demanded a 10-slice pie chart, I first mocked it up, then showed how a bar ranked view told the story faster. We agreed to the bar plus a cumulative line for context. By involving her in prototypes, I delivered a design she loved while maintaining clarity.

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A line chart is a chart that shows how a value changes over time, while a scatter chart is a chart that shows the relationship between two variables. Line charts are typically used to show trends in data, while scatter charts are used to show the correlation between two variables.

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Calculated fields are created at the data source level, allowing for more flexible data manipulation before visualization. Table calculations, on the other hand, are performed at the visualization level, enabling dynamic computations based on the displayed data.

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Whereas the LTRIM feature lets you get rid of the space found on the left side of the string, the RTRIM feature can be used to get rid of the white space found on the right side of the string to the final index.

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Tableau's order of operations, sometimes called a 'query pipeline,' provides a specific way to order its filters based on user needs. These filters give Tableau a path to follow when you place inquiries and sort data. For Tableau, the order of operations is: Extract filters, Data source filters, Context filters, Dimension filters, Measure filters, Table calc filters.

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Create a One-to-Many relationship by CustomerID in Customers → CustomerID in Orders. Syntax: Customers[CustomerID] 1 → * Orders[CustomerID]

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I start by thoroughly assessing the data sources to ensure they are relevant and accurate. Then, I clean and transform the data to meet the specific needs of the visualization, addressing any inconsistencies or missing values along the way.

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Create a drillthrough page, add the drillthrough field, and right-click a data point to navigate to the detailed page.

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| Basis | Reference Band | Bollinger Band | |---|---|---| | Definition | A Reference Band is a visual aid that highlights a range (between two constant or computed values) on a chart. | Bollinger Bands are a type of analytic band that show volatility by placing bands above and below a moving average. | | Purpose | Used to emphasize a fixed range of values such as highlighting min–max, average–standard deviation or custom ranges. | Used to measure market or data volatility and identify overbought/oversold conditions in time-series data. | | Data Dependency | Static or semi-dynamic based on chosen calculations (e.g., avg ± fixed range). | Dynamic, calculated based on moving averages and standard deviations of the data. | | Visualization | Shaded region between two lines across the chart. | Two lines plotted around a central moving average line. | | Use Case | Highlighting thresholds, performance ranges or tolerance limits in dashboards. | Tracking variation and volatility trends, especially in financial/stock data analysis. |

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To integrate Tableau with a website, developer needs to have complete understanding of Javascript API for tableau. It contains all the types of functions required to view and control a tableau worksheet and dashboard directly from the website instead of interacting directly with the worksheet. Tableau has provided a complete list of functions used in Javascript API and implementation of some of the important functions is explained in the tutorial section also which is free for all users. All the tableau dashboards or worksheets when published on tableau public or online or server are integrated with the Javascrip API by default developer only needs to call that API in the HTML code and start interacting with it.

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To compute a running or cumulative sum of a measure within a given window or range, use Tableau's 'WINDOW_SUM' function. To implement it : - Create a calculated field and in the editor write the 'WINDOW_SUM' function. WINDOW_SUM(SUM([measure]), [start], [end])' - The optional arguments [Start] and [End] specify the window or range for the total. They can be configured to limit the scope of the calculation. Drag and drop the fields to the shelf to add visualization.

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Look for: Commitment to continuous learning and professional development. What to Expect: Mention of resources like Microsoft's Power BI blog, community forums, webinars, and certifications to keep up-to-date with new features and best practices.

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The major building blocks of Power BI are: Datasets: Dataset is a collection of data gathered from various sources like SQL Server, Azure, Text, Oracle, XML, JSON, and many more. With the GetData feature in Power BI, we can easily fetch data from any data source. Visualizations: Visualization is the visual aesthetic representation of data in the form of maps, charts, or tables. Reports: Reports are a structured representation of datasets that consists of multiple pages. Reports help to extract important information and insights from datasets to take major business decisions. Dashboards: A dashboard is a single-page representation of reports made of various datasets. Each element is termed a tile. Tiles: Tiles are single-block containing visualizations of a report. Tiles help to differentiate each report.

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Data blending is a technique to combine different data sources on a single plane. Here individuals can easily analyze and visualize data from different databases. It is the advanced approach of integrating data stores. Let's take two data sources in which one shows the annual sales of the company and the other the profit and loss of that company. Working on these data banks will not be possible by using simple joins. This problem can be resolved by data blending, where all the information of the sales will be blended with profit and losses in a proper manner. The result of this data will be stored in a single sheet and will be analyzed or visualized using simple joins.

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A pie chart is a chart that shows data as a circle divided into slices, while a donut chart is a chart that shows data as a ring divided into slices. Pie charts are typically used to show the composition of a category, while donut charts are used to show the composition of a category with a hole in the center.

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I would use the following steps to carry out dynamic filtering with Power BI: Set up the data Publish a report to Power BI Publish the report to the group workspace Make a filter link Make a calculated column using a DAX formula to define the values of the column Test and publish the overview report

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Power BI has several key components, each serving a different purpose to help you work with data: - Power BI Desktop: This is a Windows application where you can make reports by connecting to data sources, transforming data, building data models, and creating visualizations. - Power BI Service: An online platform where you can view and share reports and create dashboards. - Power BI Mobile: Mobile apps for iOS, Android, and Windows that allow you to access and interact with your Power BI reports and dashboards on the go. - Power BI Gateway: A tool that allows you to connect on-premises data sources to Power BI Service for scheduled refreshes and live queries. - Power BI Report Server: An on-premises report server where you can publish and manage Power BI reports alongside traditional paginated reports. - Power BI Report Builder: A tool for authoring paginated reports and publishing them to Power BI Service. Paginated reports are optimized for printing and PDF generation. - Power BI Embedded: A service that allows developers to embed Power BI reports and dashboards into their own applications, providing interactive data visualizations to users.

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They are Named areas to the left and top of the view. You build views by placing fields onto the shelves. Some shelves are available only when you select certain mark types.

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I use Performance Analyzer to measure visual load times. I benchmark after each optimization, comparing metrics like query duration and page load time. I also use DAX Studio for detailed query analysis.

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GetData offers data connectivity to various data sources. Connect data files on your local system. The supported data sources are: - File: Excel, Text/CSV, XML, PDF, JSON, Folder, SharePoint. - Database: SQL Server database, Access database, Oracle database, SAP HANA database, IBM, MySQL, Teradata, Impala, Amazon Redshift, Google BigQuery, etc. - Power BI: Power BI datasets, Power BI dataflows. - Azure: Azure SQL, Azure SQL Data Warehouse, Azure Analysis Services, Azure Data Lake, Azure Cosmos DB, etc. - Online Services: Salesforce, Azure DevOps, Google Analytics, Adobe Analytics, Dynamics 365, Facebook, GitHub, etc. - Others: Python script, R script, Web, Spark, Hadoop File (HDFS), ODBC, OLE DB, Active Directory, etc.

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Content packs in Power BI refer to the content you have in Power BI. In the pack, you'll have a glimpse of the data and reports you have. Packs, including your reports or datasets, can be shared with others in your team.

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I recall a situation when I was working on a project for a major retail client. They had a vast amount of sales data, and I was tasked with creating a Tableau dashboard to visualize patterns and make recommendations for their marketing team. The challenge was that the client's marketing director, who is a non-technical person, needed to understand our findings to make informed decisions. To tackle this situation, I first made sure that I understood the key insights myself and was able to summarize them in simple language. I then adjusted my communication style by using analogies and straightforward terms to break down the complexity. For instance, I compared the sales trends to a rollercoaster ride. I described the ups and downs of the sales data as peaks and valleys, which made it easier for the marketing director to grasp the concepts. During a presentation, I used simple and clear visuals to support my explanation and highlight the trends that mattered most. I also encouraged questions and made sure to provide answers in a non-technical language, ensuring the stakeholder's understanding. In the end, the marketing director was able to make data-driven decisions based on our insights, and the company saw a significant improvement in their marketing campaigns' performance. The key takeaway here is to always adjust your communication style based on your audience's level of understanding and be prepared to answer questions in a way that makes the insights comprehensible and actionable.

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If you want to capture a configured view of your report's current state, you can use the bookmark feature to achieve this. Default bookmarks capture specific elements of your reports, including slicers and filters.

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Below are a few charts that we should avoid.

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To publish a report in Power BI, make sure it's ready and saved in Power BI Desktop. Then, click ‘Publish' and sign in to your Power BI account. Next, pick a workspace in Power BI Service to upload the report. Alongside the report, you also publish the underlying semantic model (dataset). Once published, you can access your report in Power BI Service. Here, you can share it with others, set up scheduled refreshes, and manage permissions. Publishing your report makes it easy to collaborate and ensures everyone has access to the latest data. ? Publishing and sharing reports in Power BI is done through Power BI Service.

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I use row-level security (RLS) defined in Power BI Desktop with DAX filters based on user email or group membership. In Power BI Service, I assign roles to security groups via workspace settings. For large teams, I automate role assignment using Azure AD groups.

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Joining term is used when you are combining data from the same source, for example, worksheet in an Excel file or tables in Oracle database While blending requires two completely defined data sources in your report.

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A line chart is a chart that shows how a value changes over time, while a combo chart is a chart that combines multiple chart types, such as a line chart and a column chart. Line charts are typically used to show trends in data, while combo charts are used to show multiple aspects of data in a single chart.

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When you hover the mouse over the name of a column, you will get a triangle symbol. When you click the triangle symbol, you will have a lot of options over there. One of those options is ‘hide'. When you click on this, the column can be hidden.

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Connect to Azure Data Lake, Databricks, or Hadoop using DirectQuery or composite models.

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Three main views are there: - Report View: It allows users to add visualization elements and additional report pages to publish on the portal. - Data View: In this view, data shaping is done using Query Editor tools. - Model View: It allows users to manage relationships between complex datasets.

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Tableau's analytic pane lets you easily access our everyday analytics data objects. It allows dragging trend lines, references, outliers, forecasts, and other elements from the analytics pane.

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I start with the date table. Time intelligence does not work reliably without a proper date dimension. I make sure the model has a continuous date table with no gaps and with columns like Year, Quarter, Month, and Week. The Date column must contain every date in the range. Then I mark it as the official Date Table in Power BI. Without a contiguous date column, functions like SAMEPERIODLASTYEAR won't behave correctly. Once the date table is in place, I build the base measure first: Total Sales = SUM(Sales[Amount]) Then I create comparison measures. For Year-over-Year: YoY Sales = [Total Sales] - CALCULATE( [Total Sales], SAMEPERIODLASTYEAR(DateTable[Date]) ) For Quarter-over-Quarter: QoQ Sales = [Total Sales] - CALCULATE( [Total Sales], DATEADD(DateTable[Date], -1, QUARTER) ) For Month-over-Month: MoM Sales = [Total Sales] - CALCULATE( [Total Sales], DATEADD(DateTable[Date], -1, MONTH) ) After absolute differences, I usually create percentage change measures. I use DIVIDE instead of the division operator to handle division-by-zero safely. For example: YoY % = DIVIDE( [YoY Sales], CALCULATE([Total Sales], SAMEPERIODLASTYEAR(DateTable[Date])) ) Now, for dynamic selection, I create a disconnected parameter table with values like YoY, QoQ, and MoM. This table does not have a relationship with the sales table. It only drives measure selection. Then I create a switching measure: Selected Comparison = SWITCH( SELECTEDVALUE(PeriodTable[Period]), "YoY", [YoY Sales], "QoQ", [QoQ Sales], "MoM", [MoM Sales] ) I place the Period column in a slicer. When the user changes the slicer, the measure switches dynamically. To improve readability, I add conditional formatting. For example, I apply icon formatting so positive values show an upward arrow and negative values show a downward arrow. I usually pair this with color formatting to make trends immediately visible. To summarize, here's what I do: a properly structured date table, clean time intelligence measures, safe percentage calculations using DIVIDE, and a disconnected parameter table to control dynamic behavior. Once those pieces are in place, the report becomes flexible without complicating the model.

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GetData is a feature of Power BI that enables the user to import data from its original source.

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The major differences between Power BI and Tableau are: - While Power BI uses DAX for calculating columns of a table, Tableau uses MDX (Multidimensional Expressions). - Tableau is more efficient as it can handle a large chunk of data while Power BI can handle only a limited amount. - Tableau is more challenging to use than Power BI.

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A gauge is a visual component that shows a single value on a gauge, while a card is a visual component that shows a single value. Gauges are typically used to show progress toward a goal or target, while cards are used to show summarized data.

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A Power BI workspace is a collaborative environment. They are used to organize reports, dashboards, semantic models (datasets), and dataflows into collections. A workspace owner can control access by assigning workspace roles to other users. It acts as a central hub for team projects and data analysis, enabling collaboration and efficient data management.

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A card is a visual component that shows a single value, while a gauge is a visual component that shows a single value on a gauge. Cards are typically used to show summarized data, while gauges are used to show progress towards a goal or target.

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An AI-powered assistant that creates dashboards, generates DAX formulas, and provides insights using natural language.

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AIR screens candidates 24/7, conducts initial interviews in 16 languages, and time-to-fill dropped from 45 to 12 days for hiring 500+ nurses per quarter.

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Example: Calculating Year-to-Date (YTD) sales using TOTALYTD() for better business insights.

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Multi-tenancy is handled with different methods including Row Level Security (RLS) for data restrictions, building projects and permissions for each tenant and deploying a combination of workbook and data sources for each tenant.

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Power Q&A in Power BI is a feature that lets users ask questions about their data in natural language and get instant answers in the form of charts or visuals. Instead of writing queries, you can type (or even speak) questions like "Total sales by region" or "Top 5 products by revenue" and Power BI automatically generates the appropriate visualization. - Uses natural language processing (NLP). - Suggests relevant questions as you type. - Provides instant, interactive visuals. - Makes data exploration simple for non-technical users.

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Follow these steps to plot geographical data: 1. Ensure your data contains geographic fields (e.g., Country, State, City, or Latitude/Longitude). 2. Assign the appropriate geographic role to the field. 3. Double-click the geographic field or drag it to the canvas. 4. Customize the map with marks, colors, and tooltips as needed.

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- Star: denormalized, simple - Snowflake: normalized, complex relationships

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To create a custom visual in Power BI, you can use the Power BI Developer Tools to build a custom visual using HTML, CSS, and JavaScript. Once the visual is created, it can be imported into Power BI and used in reports and dashboards.

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On the main page, you would have the “connect to” pane on the left side. From there, you can select “Microsoft Excel”

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The three major versions of Power BI are as follows: - Power BI Desktop: The free interactive tool that connects multiple data sources, transforms data, and creates visualized reports. - Power BI Premium: The premium version is used for larger organizations with a dedicated storage capacity for each user. With premium, data sets up to 50GB storage capacity can be hosted along with 100TB storage on the cloud as a whole. It costs $4995 per month. - Power BI Pro: With the pro version, you get full access to the Power BI dashboard, creation of reports, along with unlimited sharing and viewing of reports. You also have a storage limit of 10GB per user.

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Power BI provides several benefits, including the ability to visualize and analyze data in real-time, easy integration with other Microsoft products, easy data sharing and collaboration, and the ability to create customized reports and dashboards.

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You can see top five and bottom five sales with the help of these functions: - Drag ‘customer name' to row and sales to the column. - Sort Sum(sales) in descending order. - Create a calculated field ‘Rank of Sales'.

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CALENDAR() creates a date table with a specified start and end date. CALENDARAUTO() automatically detects the date range from the data model.

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I structure reports with a summary page for KPIs, drill-through pages for details, and bookmarks for navigation. I use annotations and tooltips to explain trends, guiding users from high-level insights to root causes.

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We can also download selected sheets into PDF format, but while generating PDF, web page objects won't be included.

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Data lineage in Power BI provides visibility into the data journey - where it comes from, where it moves, and how it's transformed. It's crucial for understanding data sources, improving data quality, managing data transformations, ensuring compliance, and more. Understanding data lineage helps in tracing data issues back to their source, ensuring data integrity, and maintaining compliance with data governance standards.

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There are three different views in Power BI, each of which serves another purpose: Report View – In this view, users can add visualizations and additional report pages and publish the same on the portal. Data View – In this view, data shaping can be performed using Query Editor tools. Model View – In this view, users can manage relationships between complex datasets.

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CORR is a correlation function that provides a correlation between two distinct variables ranging from -1 to 1.

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Azure Synapse is a unified analytics platform for large-scale data processing. Azure Analysis Services is a semantic model engine for tabular models. Synapse is for data warehousing, while AAS is for OLAP and reporting.

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A data modeling design with a central fact table connected to multiple dimension tables, optimized for query performance.

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Use slicers, timeline filters, and sync slicers across multiple pages for dynamic interactivity.

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Common challenges include inconsistent formatting, merged cells, and missing headers. I use Power Query to unpivot, clean, and standardize data. I also ensure Excel files are structured as tables for reliable imports.

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Power BI can connect to: - Files: Excel, CSV, XML, JSON. - Databases: SQL Server, MySQL, PostgreSQL, Oracle. - Cloud Services: Azure, Google Analytics, Salesforce. - APIs: REST, OData.

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In one of my projects, the sales team needed a consolidated view of regional performance across five product lines. They were working with multiple Excel files that were manually updated every week. Reporting took hours, and numbers often didn't match across teams. I started by understanding what decisions the report needed to support. Leadership wanted visibility into regional sales, quota attainment, YoY growth, and salesperson performance. So I clarified KPIs before touching the data. For data sources, I connected to SQL Server for transactional sales data, SharePoint for targets and budget data, and an Excel file that contained manual adjustments. I kept each source separate initially and cleaned it in Power Query. I standardized column names, aligned data types, and removed unnecessary fields early. After cleaning, I designed a star schema. I created a central Sales fact table and dimension tables for Product, Region, Date, and Salesperson. This improved performance and made DAX calculations more predictable. In the modeling layer, I built around 15 measures. These included Total Sales, YoY growth, quota attainment percentage, and a rolling three-month average. I implemented dynamic Row Level Security so each regional manager could only see their own region. That required a security mapping table tied to USERPRINCIPALNAME(). For the report design, I created a four-page layout: - An executive summary with KPIs and trend visuals - A regional drilldown page - A product-level performance analysis - A salesperson leaderboard I used bookmarks to allow users to toggle between monthly and quarterly views without navigating away from the page. Once development was complete, I published the report to a dedicated workspace. I configured scheduled refresh using an on-premises gateway for the SQL source and ensured credentials were securely managed. I also set up email subscriptions for leadership so they received automated updates after refresh. The impact was measurable. Weekly reporting effort dropped from around eight hours of manual consolidation to roughly 15 minutes of review time. Data accuracy improved because we eliminated spreadsheet-based calculations and manual copy-paste errors.

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Resposta de referência

Businesses use Power BI in tons of different ways, but some of the most valuable applications I've seen include: - Business performance monitoring: Teams track KPIs, departmental goals, and project statuses through interactive dashboards, helping everyone see exactly how things are going in real-time. - Decision-making and strategy: By turning raw data into clear, visual insights, leaders can quickly see what's working, spot risks or opportunities, and make better-informed decisions. - Customer insights with AI: Companies use Power BI's built-in AI capabilities to understand customer behavior, predict trends, and improve customer satisfaction; this makes marketing and sales efforts smarter. - Financial analytics and forecasting: Businesses analyze financial data, manage budgets, and forecast future outcomes easily, thanks to Power BI's intuitive forecasting tools and automated analytics. - Collaboration and transparency: Power BI dashboards can be securely shared with team members based on their roles, helping everyone easily access exactly the information they need without confusion or delays. - External reporting and engagement: Many organizations embed attractive and interactive Power BI visuals directly into websites or apps, clearly showcasing their performance or products to customers and stakeholders.

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Resposta de referência

To create a custom visual in Power BI using HTML, you can use the "Custom Visual" feature to write JavaScript code that generates the visualization using HTML and CSS. Once the code is written, you can add it to your report and use it like any other visual.

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Resposta de referência

A scatter plot is a visual representation of with the help of which we can understand the relation between two continuous variables.

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Resposta de referência

A direct query allows Power BI to connect directly to a data source and retrieve data in real-time, while an import query retrieves data from a data source and stores it in the Power BI data model. Direct queries are typically used for large datasets that are frequently updated, while import queries are used for smaller datasets that do not change frequently.

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Resposta de referência

Step 1: Go to public.tableau.com and enter your e-mail address and click “ Download the App “. Step 2: After downloading the file, run the file and follow the prompts to install Tableau. Step 3: Now, you can see the Tableau shortcut on your desktop. Step 4: Double click on the icon, to load Tableau public. Now you see the screen below.

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Resposta de referência

Deciding between a bar chart and a line chart depends on the nature of your data and the insights you want to convey. Both charts are versatile and widely used, but they have different strengths and use cases. Bar charts are great for:1. Comparing categorical data or discrete values. 2. Showing data with negative values. 3. Visualizing part-to-whole relationships, such as proportions or percentages. 4. Emphasizing individual data points. In my experience, I'd use a bar chart when I want to compare sales across different product categories or visualize the revenue generated by each salesperson. Line charts, on the other hand, are more suitable for:1. Displaying trends or patterns over time (time series data). 2. Visualizing continuous data. 3. Comparing multiple series or categories over time. 4. Showing the relationship between two continuous variables. For example, I would use a line chart to analyze the monthly sales trend for the past year or compare the sales performance of multiple product categories over time. In summary, choose a bar chart when you want to compare discrete or categorical data, and opt for a line chart when you need to display trends or relationships over time.

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Resposta de referência

To troubleshoot a slow Power BI report, consider the following steps: - Analyze and optimize the data model by removing unused columns and tables. - Check the performance of DAX queries and optimize them if necessary. - Review the number and complexity of visuals on each page. - Verify the performance of data sources and connections. - Use Power BI Performance Analyzer to identify and resolve bottlenecks.

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Resposta de referência

Power BI doesn't let you use large files, as its maximum file size is 1GB. You also can't use many data sources that function with real-time connections, and the data cannot be cleaned easily.

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Resposta de referência

Not necessarily. One of the best things about Tableau is that it's designed to be user-friendly and doesn't require heavy coding. That said, knowing some basic SQL or scripting (like Tableau's calculated fields) can give you an edge. Interviewers might ask about logical functions or how you'd manipulate data within Tableau.

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Resposta de referência

Calculated columns are added to tables and store values row by row. Measures are not stored. They calculate results based on filters and visuals. Calculated columns use more memory. Measures are better for performance. Use calculated columns when you need row-level logic in tables (like age from DOB), and measures when you need aggregated insights (like total sales).

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Resposta de referência

A) TODAY()

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Resposta de referência

Power BI uses a tabular model with DAX for calculations, while Tableau uses a relational model with table calculations and LOD expressions. Power BI enforces star schema more strictly, while Tableau is more flexible with relationships.

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Resposta de referência

Sheet (Worksheet): A sheet is the basic building block in Tableau where you create a single visualization, such as a bar chart, line chart, or map. It is used to analyze data and build individual charts. Dashboard: A dashboard is a collection of multiple worksheets combined in one view. It allows users to see different visualizations together and interact with them through filters, actions, and highlights. Story: A story is a sequence of dashboards or worksheets arranged in a specific order to present data insights as a narrative. It is used to guide viewers through a step-by-step explanation of the analysis.

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Resposta de referência

On Tableau desktop version 2019.2, access the menu on the Data pane and click on ‘Create > Calculated Field'. Name the field and create the required formula.

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Resposta de referência

A calculated column is a newly inserted column with values determined by a DAX expression that is added to a table in the data model. The computed values can be visualised after being saved in the data model. Conversely, a measure is a dynamic computation that is carried out in response to the question, taking into account the present context of the report or visualisation. Measures are computed instantly rather than being kept in the data model.

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Resposta de referência

| Aspect | Calculated Columns | Calculated Tables | Measures | |---|---|---|---| | Definition | Adds a new column to an existing table using a DAX formula. | Creates a new table using DAX expressions instead of pulling from a data source. | Performs on-the-fly calculations using DAX functions. | | Where Created | Can be created in both Report View and Data View. | Can be created in both Report View and Data View. | Can only be created in Report View. | | Use Case | Useful when data from the source isn't in the required format (e.g., splitting full names into first/last names). | Helpful for storing intermediate or user-requested data inside the model. | Best for business calculations like sales forecasting, running totals, growth %, YOY comparisons, etc. | | Storage | Stored in the model and increases data size. | Stored in the model and increases data size. | Not stored and calculated dynamically, so they don't increase model size. | | Performance | Can slow down model performance if many columns are added. | May impact performance depending on table size. | More efficient since they calculate results on demand. |

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Resposta de referência

Power Query is a data connection technology that enables users to discover, connect, combine, and refine data across various sources. In Power BI, Power Query is used for data transformation and preparation, allowing users to clean, reshape, and merge data before loading it into the data model.

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Resposta de referência

I would use DirectQuery mode. It lets Power BI fetch data in real time from the SQL Server without storing it in the model. I would also monitor query performance using SQL Profiler.

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Resposta de referência

To create a custom visual in Power BI using D3.js, you can use the "Custom Visual" feature to write JavaScript code that generates the visualization using the D3.js library. Once the code is written, you can add it to your report and use it like any other visual.

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Resposta de referência

Data can be refreshed in Power BI in the following manner: - To manually update data in Power BI Desktop, click the "Refresh" button on the Home tab to update your report with the latest information from your sources. - You can choose frequency like daily or weekly when you schedule automatic data refresh for published reports in the Power BI Service. - In the Power BI Service, dataflows can be scheduled for refresh to keep shared datasets current. - Data is always real-time for DirectQuery and Live Connection and doesn't need to be manually refreshed. - To automate data refresh processes and guarantee data accuracy, use Power BI Gateway, Power Automate, APIs or PowerShell.d

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Resposta de referência

- Report View — Create and customize visualizations. - Data View — Explore and transform data. - Model View — Define relationships between tables.

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Resposta de referência

In the Format pane, select Conditional Formatting for a field. I use rules based on values, percentages, or DAX measures. For example, I color cells red if sales are below target.

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Resposta de referência

Data blending issues in Tableau can be tricky, but I've found that taking a systematic approach can help resolve them. My process includes: 1. Verifying the relationship between data sources: I start by checking if the relationship between the primary and secondary data sources is correctly defined using the appropriate linking fields. 2. Ensuring data types match: In my experience, data blending issues can arise when the linking fields have mismatched data types. I verify that the data types of the linking fields are consistent across both data sources. 3. Confirming the aggregation level: From what I've seen, data blending problems can occur when the granularity of the data sources doesn't match. I ensure that the aggregation level of the blended data is appropriate for the analysis. 4. Handling null values: I've found that null values in the linking fields can cause data blending issues. I address this by either filtering out the null values or using calculations to handle them appropriately. 5. Reviewing calculations and table calculations: I examine any calculations or table calculations involving blended data to ensure they're accurate and functioning as intended. 6. Testing the blended data: I test the blended data by creating visualizations and comparing the results with the expected output. If there's a discrepancy, I revisit the data blending setup and make any necessary adjustments. By following this approach, I can effectively resolve data blending issues in Tableau.

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Resposta de referência

- Reduce data using filters before loading. - Use Import Mode instead of DirectQuery. - Remove unnecessary columns. - Use Aggregations for summary tables.

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Resposta de referência

Calculated columns are added to tables and store values row by row. Measures are not stored. They calculate results based on filters and visuals. Calculated columns use more memory. Measures are better for performance.

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Resposta de referência

- Use DirectQuery instead of Import Mode. - Apply data aggregations. - Implement incremental refresh.

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Resposta de referência

SELECT MAX(Mark) FROM StudentTable WHERE Mark < (SELECT MAX(Mark) FROM StudentTable)

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EARLIER(): Access row context in calculated columns. VAR: Stores intermediate values in a DAX expression for reuse.

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The 3 edit interaction options are Filter, Highlight, and None. Filter: It completely filter a visual/tile based on the filter selection of another visual/tile. Highlight: It highlight only the related elements on the visual/tile, gray out the non-related items. None: It ignore the filter selection from another tile/visual.

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Resposta de referência

The reports that Power BI generates contain visual features similar to filters that help users filter out certain data. These visual filters are known as slicers. With a slicer, users can choose certain values and select them while analyzing the report.

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Resposta de referência

Look for: Understanding of data gateways, scheduled refresh settings, and troubleshooting refresh issues. What to Expect: Explanation of configuring data sources for refresh, setting up data gateways, and managing refresh schedules to ensure up-to-date reports.

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Resposta de referência

We can show how sales this year compare to last year using calculated fields: YoY Growth = ([Sales] - LOOKUP([Sales], -1)) / LOOKUP([Sales], -1) This compares sales with the previous year.

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Resposta de referência

Despite both being two of the best data analytics tools, there are some critical differences between Tableau and Power BI. Tableau can handle large data sets and is ideal for experts. It has an intricate user interface and is cloud-compatible, as well. On the other hand, Power BI can only cope with smaller data sets, but it's suitable for both experts and beginners, as it has a slightly more simple interface. In addition to that, Power BI doesn't easily support cloud integrations.

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Resposta de referência

The main engine behind power pivot is the xVelocity in-memory analytics engine. It can handle large amount of data because it stores data in columnar databases, and in memory analytics which results in faster processing of data as it loads all data to RAM memory.

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Resposta de referência

Analysing and evaluating data to determine its distribution, quality, and structure is known as data profiling. Power Query, which offers several data profiling features like column statistics, data type recognition, and error flagging, may be used in Power BI to accomplish data profiling. Finding problems with data quality, inconsistencies, and outliers is crucial since they can affect the dependability and accuracy of analysis and reporting.

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Resposta de referência

Tableau offers 80+ native data connectors to connect with different types of data sources. The most common connections include Excel, Text/CSV files, SQL Server, MySQL, Oracle, and PostgreSQL. It also supports cloud data sources such as Google BigQuery, Amazon Redshift, and Snowflake. Tableau can connect to web data using Web Data Connectors and APIs. Additionally, users can connect to published data sources from Tableau Server or Tableau Cloud for centralized data access.

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Resposta de referência

Combines DirectQuery and Import Mode for flexibility and efficiency in large datasets.

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Resposta de referência

Designing effective dashboards in Power BI involves more than just aggregating data into visuals. It requires thoughtful planning and design to ensure that the dashboard is user-friendly, informative, and actionable. A well-designed dashboard allows users to quickly grasp essential insights necessary for decision-making, through a combination of simplicity, consistency, and relevance. This involves maintaining a clean and uncluttered layout, using consistent design elements across visuals, and ensuring every data element serves a specific purpose. Incorporating visual hierarchy is key to directing attention to the most important information first, which can be highlighted through strategic placement and distinct coloring. For example For a dashboard monitoring real-time sales performance by region, you might place the most current metrics prominently at the top, perhaps using a gauge or ticker for instant visibility. Then quarterly trends could be shown using a line chart below the real-time data, allowing users to spot patterns at a glance. TL;DR Effective dashboard design ensures that users can quickly and easily interpret key metrics and insights, leading to more informed and timely decision-making.

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Resposta de referência

Four main refresh options are available in Power BI: - Package/OneDrive refresh: This synchronizes Power BI desktop or Excel file between the Power BI service and OneDrive - Data/Model refresh: This means scheduling the data import from all the sources based on either refresh schedule or on-demand. - Tile refresh: Refresh the tiles' cache on the dashboard every time the data changes. - Visual container refresh: Update the reports' visuals and visual container once the data changes.

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Resposta de referência

Extract connection is better than live connection because extract connection can be used from anywhere, anytime without connecting to the database. We can construct our own visualizations on it irrespective of the database connection.

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Resposta de referência

In simple terms, Power BI is an enterprise Microsoft app for business analytics. Using Power BI enables you to convert several data sources unrelated to each other into comprehensive, structured data that provides you with valuable insights. The data might then be stored in an Excel spreadsheet or on the cloud, and you can share it with others.

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Resposta de referência

Data extracts are the first copies or subdivisions of the actual data from original data sources. The workbooks using data extracts instead of those using live DB connections are faster since the extracted data is imported in Tableau Engine.After this extraction of data, users can publish the workbook, which also publishes the extracts in Tableau Server. However, the workbook and extracts won't refresh unless users apply a scheduled refresh on the extract. Scheduled Refreshes are the scheduling tasks set for data extract refresh so that they get refreshed automatically while publishing a workbook with data extract. This also removes the burden of republishing the workbook every time the concerned data gets updated.

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Resposta de referência

A multi-row card is a visual component that shows data in a tabular format but with the ability to display multiple rows of data for each category, while a table is a visual component that shows data in a tabular format. Multi-row cards are typically used to show summarized data, while tables are used to show detailed data.

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Resposta de referência

Yes. I usually start by removing blank rows. Then I fix column names, change data types, and remove duplicates. I might also split columns or merge them depending on the data format. Power Query lets you apply all these steps in a clean, step-by-step interface without writing code.

133

Resposta de referência

To create a custom theme in Power BI using JSON, you can use the "Themes" feature to define the colors, fonts, and other visual elements that you want to use. Once the theme is created, you can save it as a JSON file and import it into Power BI.

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Resposta de referência

Tableau allows its user to join a maximum of 32 tables.

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Resposta de referência

Four main refresh options are available in Power BI: Package/OneDrive refresh: This synchronizes Power BI desktop or Excel file between the Power BI service and OneDrive Data/Model refresh: This means scheduling the data import from all the sources based on either refresh schedule or on-demand. Tile refresh: Refresh the tiles' cache on the dashboard every time the data changes. Visual container refresh: Update the reports' visuals and visual container once the data changes.

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Resposta de referência

Creating a dashboard is also considered as reporting because once you are done designing the dashboards per client's requirement it can be used in ppt or pdf or any required filetype and its compatibility with the view created. These dashboards can be interactive so that the client can set the filters and parameters to view custom charts under different conditions.

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Resposta de referência

The following are the Building Blocks (or) key components of Power BI: Visualizations: Visualization is a visual representation of data. Example: Pie Chart, Line Graph, Side by Side Bar Charts, Graphical Presentation of the source data on top of Geographical Map, Tree Map, etc. Datasets: Dataset is a collection of data that Power BI uses to create its visualizations. Example: Excel sheets, Oracle or SQL server tables. Reports: Report is a collection of visualizations that appear together on one or more pages. Example: Sales by Country, State, City Report, Logistic Performance report, Profit by Products report etc. Dashboards: Dashboard is single layer presentation of multiple visualizations, i.e we can integrate one or more visualizations into one page layer.

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Resposta de referência

DAX (Data Analysis Expressions) is a powerful formula language used within Power BI to create custom calculations, measures, and calculated columns in data models. I think of it as similar to Excel formulas, but specifically designed for Power BI's data models. With DAX, I can perform advanced analytics, like creating custom metrics, calculating year-over-year growth, or filtering data dynamically. It's also great for building measures that can instantly adapt to different user interactions on my reports and dashboards.

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Resposta de referência

Power BI Free is limited to personal use, with no sharing or collaboration features. Power BI Pro allows sharing, collaboration, and scheduled refreshes. Premium offers higher capacity and advanced features.

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Resposta de referência

Tableau Public is a free version of Tableau that allows users to create and share data visualizations online. It is mainly used for learning, practice, and publishing visualizations to the public. All dashboards created in Tableau Public are saved on the Tableau Public website and are accessible to everyone, so it is not suitable for confidential or sensitive data. It is commonly used by students, analysts, and professionals to showcase their portfolio and data storytelling skills.

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Resposta de referência

In Tableau, a context filter is a special type of data filter that allows you to control the order in which filters are applied to the data. It creates a temporary table containing only the data that passes through the context filter, and all subsequent filters are applied to this reduced dataset. Context filters are particularly useful when dealing with complex data relationships and large datasets, as they help improve performance and optimize query execution. Steps to create a context filter in Tableau: Connect to Data: Start by connecting to your data source in Tableau and importing the relevant data. Create Initial Filters: Before creating the context filter, you may want to add some initial filters to your visualization to narrow down the data. Right-click on a Filter: In the data pane or on the Filters shelf, right-click on the filter you want to convert to a context filter. Select "Add to Context": From the context menu that appears, select "Add to Context." This action will change the filter icon, indicating that it has been added to the context. Order of Filters: Move the context filter to the top of the list of filters on the Filters shelf. This ensures that it will be applied first when the visualization is computed. Recompute the Visualization: After adding the context filter, recompute the visualization by clicking the "Refresh" or "Run" button on the toolbar to see the impact of the context filter on your data. By adding a context filter, you're instructing Tableau to create a temporary table with the data that meets the conditions of the context filter, and then apply subsequent filters only to this reduced dataset. This can significantly improve performance, especially when dealing with complex data models and large datasets. Keep in mind that using context filters should be done with consideration, as they can impact the accuracy of certain calculations and aggregations, depending on the order in which filters are applied. It is essential to understand the data and the specific requirements of your analysis before applying context filters.

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Resposta de referência

Handling null values is important for data accuracy and visualization clarity. Some of the ways to handle null values are: - Replace Null Values: We can replace null values by right click on the field containing null values, going to "Edit" then clicking "Replace Null". Enter the desired replacement value and then click "OK". - Filter out Null values: We can filter out null values by creating a filter to exclude null values from your visualization. Drag the field with null values to the "Filter" shelf and uncheck the "Null" option. - Handling Null Values in Calculations: Using Tableau functions like 'ISNULL()" or "ZN()" in calculations to handle null values.

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Resposta de referência

It is a function in Tableau that showcases two scales of two measures in a single graph. This is very similar to the function found on Microsoft Office products where a single graph has line and bar elements. In most cases, it has either two X or two Y axes. A dual-axis is typically used to show trend lines and historical data. An example would be total revenue vs profit across 12 months.

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Resposta de referência

Following are some of the important Components of SSAS: OLP Engine An OLAP Engine is used to extensively run the ADHOC queries at a faster pace by the end-users Data Drilling It describes data Drilling in SSAS as the process of exploring details of the data with multiple levels of granularity.

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Resposta de referência

A .twb file contains information on all the sheets, dashboards and stories, but it won't contain any information regarding data source. Whereas .twbx file contains all the sheets, dashboards, stories and also compressed data sources. For saving a .twbx extract needs to be performed on the data source. If we forward .twb file to someone else than they will be able to see the worksheets and dashboards but won't be able to look into the dataset.

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Resposta de referência

Power BI Service is a cloud-based platform for: - Publishing and sharing reports securely. - Collaboration through workspaces. - Scheduling refreshes for updated reports.

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Resposta de referência

Load testing in Tableau is done to understand the server's capacity with respect to its environment, data, workload, and use. It is preferable to conduct load testing at least 3-4 times in a year because with every new user, upgrade, or content authoring, the usage, data, and workload change. Tabjolt was created by Tableau to conduct point-and-run load and performance testing specifically for Tableau servers. Tabjolt: - Automates the process of user-specified loads - Eliminates dependency on script development or script maintenance - Scales linearly with an increase in the load by adding more nodes to the cluster

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Resposta de referência

A tableau packaged data source is a zip file with extension (.tdsx) containing all the data source files(.tds) which contains all the calculated fields, groups and any other changes that have been made on the original data with original data as well. Tableau packaged data source also contains extract files (.hyper or .tde), excel files, access files. This .tdsx file can be used as a single file to handover the dataset to someone who does not have direct access to original data set.

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Resposta de referência

Yes, we can do testing in Tableau by using tools and the easiest way is using the desktop application. We need to check it before we publish it on the Tableau server.

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Resposta de referência

The different views in PowerBI are: Report View : It is the default view which shows the visualization of the data in reports. You can create multiple report pages here with a wide range of templates and visualizations.

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Resposta de referência

LOD expressions are used to perform aggregations that are more granular than the view's original level of aggregation. There are three types of LOD expressions: FIXED, INCLUDE, and EXCLUDE: - A FIXED LOD computes a value for a fixed level of dimensions, regardless of the view's other dimensions. - An INCLUDE LOD computes a value for a specified level of dimensions while also including other dimensions in the view. - Finally, an EXCLUDE LOD computes a value for a specified level of dimensions while excluding other dimensions from the view. For example, let's say we have a visualization that shows the total sales volume by region by month, but we also want to return the total sales volume by region only without aggregating at the month-level. We can use an LOD to perform the calculation. Create a calculated field and add the formula below: {FIXED [Region] : SUM([Sales])}

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Resposta de referência

By adding the same calculation to 'Group By' clause in SQL query or creating a Calculated Field in the Data Window and using that field whenever you want to group the fields. Using groups in a calculation. You cannot reference ad-hoc groups in a calculation. Blend data using groups created in the secondary data source: Only calculated groups can be used in data blending if the group was created in the secondary data source. Use a group in another workbook. You can easily replicate a group in another workbook by copy and pasting a calculation.

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Resposta de referência

Tableau is a business intelligence and data visualization tool used to analyze data and create interactive dashboards and reports. It helps transform raw data into meaningful insights using charts, graphs, and other visual elements. Tableau can connect to multiple data sources such as Excel, databases, and cloud platforms. Its drag-and-drop interface makes it easy for users to build visualizations without extensive coding. It is widely used by organizations to support data-driven decision making.

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Resposta de referência

Measures are calculations in Power BI, Power Pivot or Analysis Services that compute results dynamically based on the current filter context. Unlike columns, they aren't stored in the table, instead they are evaluated dynamically whenever you interact with visuals, slicers or filters in your report. - Created using DAX formulas. - React to filters, slicers and other visuals automatically. - Commonly used for sum, average, count, percentage or custom calculations. - Stored in the data model, not in individual rows. Example: Total Sales = SUM(Sales[Amount]) It shows the total sales dynamically based on applied filters like region or year.

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Resposta de referência

- Returns a subset of a table based on conditions. Example: FILTER(Sales, Sales[Amount] > 1000) This returns rows where Amount > 1000.

156

Resposta de referência

With “Get Data” in PowerBI, you connect to different data sources to import data for analysis and visualization. You can select from a range of various data sources to import the desired data. Eg. Text/CSV, Excel, PDF, JSON, Amazon Redshift, SQL Server database, Access database, SAP HANA database, IBM, MySQL, Oracle database, Impala, Google BigQuery,etc.

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Resposta de referência

Page shelf in tableau helps to understand multiple charts in a more friendly and useful ways. If we are getting multiple plots in a single sheet and you want to view it one by one then drag and drop the dimension which is responsible for creating multiple charts instead of a single chart to the page shelf. Then we get a option on right side to scroll through different charts one by one and analyze the data.

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Resposta de referência

Power BI connects to Azure Synapse via DirectQuery or Import. Synapse provides a unified analytics platform, and Power BI visualizes the data. I use Synapse for large-scale data processing and Power BI for interactive reporting.

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Resposta de referência

Use DirectQuery, aggregations, optimized relationships, and partitions.

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Resposta de referência

In Power BI, cloud storage is used to store data. However, Microsoft uses two cloud services: Azure SQL Database and Azure Blob Storage.

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Resposta de referência

A major difference between data blending and data joining is where your data sources are coming from. Using data blending is helpful if you bring in data from different sources with common data points. Data joining, however, uses one source for data and joins specific data points together from that source.

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Resposta de referência

I prioritize data quality by implementing automated validation checks in our ETL processes. I work closely with data engineers to ensure that data from various sources is cleansed and harmonized before it reaches Tableau. For instance, I set up alerts for anomalies and discrepancies in the data. This proactive approach helped reduce errors in our dashboards by over 40%, significantly enhancing user trust in the insights provided.

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Resposta de referência

Power BI Pro is a paid version of Power BI that allows users to create and share reports with other Power BI Pro users. Power BI Premium Per User is a higher-end version of Power BI that provides additional features, such as larger data capacity, more frequent data refreshes, and the ability to share reports with a broader audience, on a per-user basis.

164

Resposta de referência

Custom Visuals are like any other visualizations, generated using Power BI. The only difference is that it developes the custom visuals using a custom SDK. The languages like JQuery and JavaScript are used to create custom visuals in Power BI.

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Resposta de referência

Hyper is used for Tableau's in-memory Data Engine. It helps importing and analysing the data at a faster rate. It allows user to create an extract file of data set which can be considered as a compressed version of dataset containing all the data hence increasing the speed of executing different queries on dataset. It helps the user to work on big datasets with greater ease.

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Resposta de referência

I start by identifying the key message and the target audience for the visualization. Then, I use visual elements that highlight important data points and incorporate interactive features to engage users, ensuring the story is both compelling and informative.

167

Resposta de referência

A single measure, a target value, and an indication that indicates performance in relation to the objective are all displayed in a KPI (Key Performance indication) visualization. In contrast, a card visualization shows just one parameter without any performance indicator or aim.

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Resposta de referência

In healthcare, I masked PHI fields with Tableau's data-source filters and stored extracts on encrypted drives. Access logs were reviewed weekly to meet HIPAA audit requirements.

169

Resposta de referência

Data refresh issues can arise due to various factors, such as connectivity problems, data source changes, or permission issues. To handle data refresh issues: - Verify the data source credentials and permissions. - Check the gateway configuration and connectivity. - Review the refresh schedule and ensure it aligns with data availability. - Monitor and troubleshoot errors in the Power BI service or on-premises gateway.

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Resposta de referência

Whereas using Power Pivot for Excel can support an import model and calculated columns, in addition to a single directional relationship, Power BI Desktop has a few more functions: it offers two-way connectivity and combines the functions of both Pivot and Power Query. Also, Power BI Desktop offers better-quality visualizations compared with Power Query.

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Resposta de referência

Dataset: The source used to create reports and visuals/tiles. A data model (local to PBIX or XLSX) or model in an Analysis Services Server Data could be inside of model (imported) or a Direct Query connection to a source. Report: An individual Power BI Desktop file (PBIX) containing one or more report pages. Built for deep, interactive analysis experience for a given dataset (filters, formatting). Each Report is connected to atleast one dataset Each page containing one or more visuals or tiles. Dashboard: a collection of visuals or tiles from different reports and, optionally, a pinned. Built to aggregate primary visuals and metrics from multiple datasets.

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Resposta de referência

I would extract the data source and rebuild the data model in Power BI using star schema. Then recreate visuals using Power BI equivalents, convert calculated fields to DAX, and adjust filters and parameters. Testing ensures accuracy.

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Resposta de referência

Power BI Pro is a paid version of Power BI that allows users to create and share reports with other Power BI Pro users. Power BI Premium Per Capacity is a higher-end version of Power BI that provides additional features, such as larger data capacity, more frequent data refreshes, and the ability to share reports with a broader audience, on a shared capacity basis.

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Resposta de referência

A custom SQL can help a user to extract the information you need. A custom SQL query can be written after connecting tableau to a data source. Once connected to a data source, double-click the “New Custom SQL” option on the data source page. Then type or paste the SQL query to the text box and when finished click OK.

175

Resposta de referência

Tableau cannot plot null values on the-axis. So, it will display an indicator at the lower right corner of the view. Once you click on that indicator, you have options to handle null values. Below are the options available to handle null values.

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Resposta de referência

A Tableau dashboard is a collection of visualizations and worksheets that provide a consolidated view of data insights and analysis. It is a user-friendly and interactive interface that allows users to explore, interact, and gain insights from data in a visually appealing manner. Key features of a Tableau dashboard: Multiple Visualizations: A dashboard can contain multiple visualizations, such as charts, graphs, tables, and maps, organized on a single screen to provide a comprehensive view of the data. Interactivity: Dashboards are highly interactive, allowing users to drill down, filter, sort, and highlight data points to explore different aspects of the data. Data Filters: Users can apply data filters to focus on specific subsets of data, making it easier to analyze and interpret relevant information. Layout and Design: Tableau dashboards offer flexible layout and design options, allowing users to arrange visualizations, add text, images, and web pages to create a visually appealing and informative dashboard. Parameter Controls: Parameters can be added to dashboards to enable dynamic user control over calculations, filters, and other aspects of data analysis. Real-time Updates: Dashboards in Tableau are connected to live data sources or data extracts, ensuring that the visualizations update in real-time as the underlying data changes. Storytelling: Dashboards can be used to tell data-driven stories, presenting insights and findings in a logical and engaging manner. Sharing and Collaboration: Tableau dashboards can be shared with others within the organization or published to Tableau Server or Tableau Online for wider dissemination and collaboration. Tableau dashboards are widely used in data analysis, business intelligence, and data visualization projects, as they provide a clear and concise representation of complex data, enabling users to make data-driven decisions more effectively.

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Resposta de referência

Users can set up for an automatic refresh over data based on daily or weekly requirements. Users can schedule only one refresh maximum daily unless they have Power BI Pro. The Schedule Refresh section uses the pull-down menu choices to select a frequency, time zone, and time of day.

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Resposta de referência

I publish to a staging project first, QA with power users, then move to production. Permissions inherit from AD groups: Analysts can edit; Execs can view. I schedule extracts during low-traffic windows and monitor with admin views.

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| Feature | Power BI | Excel | |---|---|---| | Tabular Reports | Not ideal for creating traditional tabular reports. | Well-suited for detailed tabular reports. | | Duplicate Tables | Cannot display duplicate tables directly. | Allows users to display duplicate tables easily. | | Reports | Provides interactive and personalized reports with cross-filtering between charts. | Limited interactivity and advanced cross-filtering between charts is not available. | | Analytics | Offers easy-to-use analytics, mainly focused on data visualization. | Provides advanced analytics with complex formulas, pivot tables and statistical functions. | | Applications | Best for creating dashboards, KPIs and alerts with real-time insights. | Useful for calculations, financial models and newer charts exist but lack direct data model connections. |

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Resposta de referência

There are five different components of Power BI. - Power Pivot: Fetches and cleans data and loads on to Power Query - Power Query: Operates on the loaded data - Power Q&A: Makes it possible for users to interact with reports using simple English language - Power View: Lets users create interactive charts, graphs, maps and other visuals - Power Map: Enables the processing of accurate geographic locations in datasets

181

Resposta de referência

A stacked column chart is a chart that shows the composition of each category using stacked columns, while a 100% stacked column chart is a chart that shows the composition of each category as a percentage of the total. Stacked column charts are typically used to show changes over time, while 100% stacked column charts are used to compare the proportion of each category.

182

Resposta de referência

AIR cut screening time by 85%, reducing initial candidate assessments from 3 weeks to 2 days, and candidates prefer the conversational interviews over phone screens.

183

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Primarily, Power BI has two sources to store data: Azure Blob Storage: When users upload the data, it gets stored here. Azure SQL Database: All the metadata and system artifacts are stored here. They are stored as either fact tables or dimensional tables.

184

Resposta de referência

In power BI, you have various kinds of views viz: - Data View: Curating, exploring, and viewing data tables in the data set. Unlike, Power Query editor, with data view, you are looking at the data after it has been fed to the model. - Model View: This view shows you all the tables along with their complex relationships. With this, you can break these complex models into simplified diagrams or set properties for them at once. - Report View: The report view displays the tables in an interactive format to simplify data analysis. You can create n number of reports, provide visualizations, merge them, or apply any such functionality.

185

Resposta de referência

In Tableau, a column chart is a type of data visualization that represents data using vertical bars. Each column corresponds to a specific category or dimension, and the height of the column indicates the value of a measure associated with that category. Key features of a column chart in Tableau: Vertical Bars: The primary feature of a column chart is the vertical bars, where the length or height of each bar represents the magnitude of the associated measure. Categorical Data: Column charts are suitable for visualizing categorical data, where each category is represented by a separate column. Aggregated Values: The height of the columns can represent aggregated values such as sum, average, count, or any other measure based on the data analysis requirements. Grouped or Stacked Columns: Tableau allows users to create grouped or stacked column charts. In a grouped column chart, each category has its set of columns side-by-side, while in a stacked column chart, the columns are stacked on top of each other for each category. Color Encoding: Users can use color to encode additional information, such as differentiating between subcategories or segments within a column. Axis Labels and Titles: Column charts come with axis labels and titles to provide context and explanation for the data being visualized. Column charts are commonly used to compare values between different categories and identify patterns or trends in the data. They are effective for presenting data in a straightforward and intuitive manner, making them a popular choice for data analysis and reporting tasks in Tableau.

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Resposta de referência

Pros: - Ease of Use: Power BI has a user-friendly interface that is easy for anyone familiar with Excel to pick up - Integration: Seamless integration with other Microsoft products enhances its utility in a Microsoft-based infrastructure - Power Query: Built-in ETL tool for fetching and transforming datasets, which simplifies data preparation tasks - DAX: Formula language for defining complex calculations, which adds a layer of powerful analytics capabilities - Powerful Visualizations: Wide range of options for data presentation, making it easier to communicate insights - Regular Updates: Power BI is continuously enhanced with new features and improvements - Cost-Effective: Competitive and flexible pricing structure, making it accessible for small to medium-sized businesses. Cons: - Limited Data Export Options: Power BI provides fewer formats for exporting reports, which can be limiting for users who need specific export formats - Performance Issues with Large Datasets: Power BI can experience performance issues when working with extremely large datasets, which can impact the efficiency of data analysis - Fewer Advanced Visualizations: While Power BI features a wide variety of visualizations out-of-the-box, going beyond those can be quite difficult without custom development Understanding the pros and cons helps in assessing when and where to effectively use Power BI, ensuring it meets the specific needs of the organization. You may be asked which you would choose in a specific situation and why or why not, so be aware of these limitations.

187

Resposta de referência

- Reduce dataset size. - Use aggregations instead of row-level data. - Optimize DAX calculations using variables. - Limit the number of visuals per report page.

188

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Tableau caters to a wide range of products. The products available in the Tableau family are - Tableau Server - Tableau Desktop - Tableau Reader - Tableau Online - Tableau Public

189

Resposta de referência

A Conditional Column in Power BI is a column created based on a condition or rule applied to existing columns. It allows you to categorize or transform data without writing DAX formulas. - Created in Power Query Editor. - Values in the new column depend on conditions applied to other columns. - Useful for categorizing, grouping or flagging data. Syntax Example: if [SalesAmount] > 1000 then "High" else if [SalesAmount] >= 500 then "Medium" else "Low" Here: - If SalesAmount > 1000 → High - If SalesAmount between 500–1000 → Medium - If SalesAmount < 500 → Low

190

Resposta de referência

Data can be filtered using three types of filters in Power BI: - Drillthrough filters: With Drillthrough filters in Power BI, you can create a page in your reports. You can focus on specific entities like customers, suppliers or manufacturers. - Page-level filters: These filters are used to separate data in charts included on individual pages. - Report-level filters: These types of filters are used to simultaneously filter the charts present on all pages of a report.

191

Resposta de referência

I use DAX measures with SWITCH or SELECTEDVALUE to change titles based on slicer selections. For dynamic visuals, I use bookmarks or field parameters to toggle between charts.

192

Resposta de referência

Look for: Report design principles, performance optimization, and user experience considerations. What to Expect: Discussion on using themes and templates, optimizing visuals for performance, ensuring clarity and readability, and incorporating user feedback.

193

Resposta de referência

Create a calculated field: IF DATETRUNC('month', [Order Date]) = DATETRUNC('month', TODAY()) THEN "Latest Month" END Apply this field as a filter to keep only the latest month.

194

Resposta de referência

For reducing warehouse downtime, I'd start with stakeholder interviews to define key metrics: downtime minutes, incident type, shift. Next, I'd sketch a KPI banner, timeline, and Pareto chart. After user feedback, I'd refine colors and publish to a mobile-friendly layout, delivering actionable insights for floor managers.

195

Resposta de referência

A couple of months ago, I was working on a project for a retail client that required visualizing sales performance across multiple store locations and product categories. I created a complex dashboard in Tableau containing multiple charts and filters. However, I noticed that some of the charts were not updating correctly when certain filters were applied. To identify the issue, I first reviewed the data connections and the data source to ensure all data was being pulled correctly. Finding no issues there, I then examined the calculated fields, which led me to discover that one of the calculations was causing the inconsistency in the chart updates. I realized that a custom calculation I had created to make the categories more user-friendly was actually excluding the sales data for certain categories depending on the filter. In order to resolve the issue, I revised the custom calculation to ensure that all relevant data would be included when the user applied their filters. I then tested the updated dashboard thoroughly across multiple scenarios to ensure that the issue was indeed resolved. The end result was a much more accurate and dynamic visualization that correctly displayed the required data and allowed the client to better track their sales performance across all locations and product categories.

196

Resposta de referência

Power BI connects to a wide range of data sources, making it versatile for data analysis and visualization. Key data sources include: - Excel: Import data directly from Excel files. - SQL Server: Connect to SQL Server databases for large datasets. - SharePoint: Integrate data from SharePoint lists and libraries. - Azure: Access various Azure services like Azure SQL Database and Azure Data Lake. - Web Data: Pull data from websites using APIs. - Other Databases: Connect to databases like MySQL, Oracle, and PostgreSQL. - Online Services: Integrate with services like Google Analytics and Salesforce. - Flat Files: Import data from CSV, XML, and JSON files. - Fabric/OneLake: Access all Microsoft data platforms (warehouses, lakehouses, dataflows, semantic models) from a single point of entry. ? Power BI connects to various data sources, making it a flexible business intelligence tool.

197

Resposta de referência

I think about CALCULATE as a filter context modifier and FILTER as a table-returning iterator. CALCULATE evaluates an expression after modifying the current filter context. It takes a measure or expression as the first argument, and then one or more filters that change how that expression gets evaluated. For example: CALCULATE([Total Sales], Products[Category] = "Electronics") Here, Power BI applies the filter on Products[Category] first, then evaluates [Total Sales] in that modified context. This type of column filter is efficient because it pushes work to the storage engine. FILTER, on the other hand, returns a table. It scans a table row by row and keeps only the rows where the condition evaluates to TRUE. For example: FILTER(Products, Products[Price] > 100) This produces a filtered table, not a scalar value. I usually wrap FILTER inside CALCULATE when I need more complex logic. The key difference becomes clear when measures are involved. If my filter condition depends on a measure, I cannot use a simple column filter inside CALCULATE. In that case, I use FILTER. For example: CALCULATE( [Total Sales], FILTER(Products, [Profit Margin] > 0.2) ) Since [Profit Margin] is a measure, it needs row-by-row evaluation within FILTER. Another important concept is context transition. When I use CALCULATE inside a row context — for example, inside a calculated column or iterator — it converts the row context into a filter context before evaluating the expression. That behavior is central to how many advanced DAX calculations work. From a performance perspective, I prefer simple column filters inside CALCULATE whenever possible. They are faster and more optimized than wrapping everything inside FILTER, especially on large tables. I also use modifiers like ALL or REMOVEFILTERS inside CALCULATE when I need to clear existing filters. For example: CALCULATE([Total Sales], ALL(Products)) That removes filters from the Products table before evaluating the measure. So here's what I do: - I use CALCULATE to change the filter context. - I use FILTER when the condition is complex or depends on row-by-row logic. - I prefer column filters for performance. - I stay aware of context transition because it directly affects how the result is computed.

198

Resposta de referência

Sometimes the data present in a particular column could comprise of a lot of things. For example - “Full Name”. If we have a name such as ‘Adam Reddy'. Here, this ‘Full Name' can be divided into two parts - ‘First Name' and ‘Last Name'. For this purpose, we can use split.

199

Resposta de referência

I follow Edward Tufte's principles by decluttering visuals: no 3-D, limited color palette, and clear labeling. In a revenue dashboard, using a muted grey palette with a single blue highlight drew attention straight to underperforming regions.

200

Resposta de referência

Whenever we set a context filter, Tableau generates a temp table that needs to refresh each and every time, whenever the view is triggered. So, if the context filter is changed in the database, it needs to recompute the temp table, so the performance will be decreased.

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