Course Introduction
1.1 Introduction
1.2 What Will You Learn
Introduction to Business Analytics
2.1 Introductionto Business Analytics
2.2 Learning Objectives
2.3 Types of Analytics
2.4 Areas of Analytics
2.5 Quick Recap
Data Cleaning and Preparation
3.1 Learning Objectives
3.2 Sort and filter
3.3 Group by and subtotal
3.4 Text to Column
3.5 Removing Duplicates
3.6 Data Validation
3.7 Quick Recap
3.8 Knowledge Check
Formatting Conditional Formatting and Important Functions
4.1 Introduction
4.2 Learning Objectives
4.3 Introduction to Custiom Formatting
4.4 Custom Formatting Example
4.5 Introduction to Conditional Formatting
4.6 Conditional Formatting Example One
4.7 Conditional Formatting Example Two
4.8 Conditional Formatting Example Three
4.9 Logical Functions
4.10 Lookup and reference functions
4.11 VLOOKUP Function
4.12 HLOOKUP Function
4.13 MATCH Function
4.14 INDEX and OFFSET Function
4.15 Statistical Function
4.16 SUMIFS Function
4.17 COUNTIFS Function
4.18 PERCENTILE and QUARTILE
4.19 STDEV MEDIAN and RANK Function
4.20 Exercise Introduction
4.21 Exercise
4.22 Quick Recap
4.23 Knowledge Check
Spotlight
5.1 Spotlight
Analyzing Data with Pivot Tables
6.1 Introduction
6.2 Learning Objectives
6.3 Introduction to Pivot tables
6.4 Creating a Pivot tables
6.5 Grouping in Pivot tables
6.6 Grouping in Pivot Table Example One
6.7 Grouping in Pivot Table Example Two
6.8 Custom Calculation
6.9 Calculated Field and Calculated Item
6.10 Calculated Field Example
6.11 Calculated Item Example
6.12 Slicer introduction
6.13 Creating a Slicer
6.14 Exercise Introduction
6.15 Exercise
6.16 Quick Recap
6.17 Knowledge Check
Dashboarding
7.1 Introduction
7.2 Learning Objectives
7.3 What is a Dashboard
7.3 What is a Dashboard
7.4 Principles of a Great Dashboard Design
7.5 How to Create Charts in Excel
7.6 Chart Formatting
7.7 Tzhermometer Chart
7.8 Pareto Chart
7.9 Speedometer Chart
7.10 Create a Speedometer Chart
7.11 Stacked Column Chart
7.12 Funnel Chart
7.13 Pivot Chart
7.14 Form Controls in Excel
7.15 Interactive Dashboard with Form Control
7.16 Chart with Checkbox
7.17 Chart With Combobox
7.18 Chart With Scrollbar
7.19 Interactive Chart
7.20 Exercise Introduction
7.21 Exercise One
7.22 Exercise Two
7.23 Quick Recap
7.24 Knowledge Check
Business Analytics With Excel
8.1 Introduction
8.2 Learning Objectives
8.3 Histogram
8.4 Solver Add in
8.5 Goal Seek
8.6 Data Table
8.7 Descriptive Statistics
8.8 Exercise Introduction
8.9 Exercise
8.10 Quick Recap
8.11 Knowledge Check
Spotlight
9.1 Spotlight
Data Analysis Using Statistics
10.1 Introduction
10.2 Learning Objectives
10.3 Moving Average
10.4 Hypothesis Testing
10.5 ANOVA
10.6 Covariance
10.7 Correlation
10.8 Regression
10.9 Multiple Linear Regression
10.10 Logistic Regression
10.11 Normal Distribution
10.12 Exercise One Introduction
10.13 Exercise One
10.14 Exercise Two Introduction
10.15 Exercise Two
10.16 Exercise Three Introduction
10.17 Exercise Three
10.18 Quick Recap
10.19 Knowledge Check
Using Macros for Analytics
11.1 Learning Objectives
11.2 Using Macros for Analytics
11.3 Mean of Data Using Macros
11.4 Point Summary Using Macros
11.5 Correlation Coefficient Using Macros
11.6 Removing Duplicates Using Macros
11.7 Quick Recap
11.8 Knowledge Check
Spotlight
12.1 Spotlight
Excel remains a cornerstone for business analysis, offering powerful tools to organize, visualize, and interpret data. With features like pivot tables, charts, and advanced formulas, it enables analysts to uncover trends, track performance, and support decision-making. Functions such as VLOOKUP, IF statements, and conditional formatting streamline data manipulation, while Power Query enhances data import and transformation. For financial modeling, forecasting, or KPI tracking, Excel’s flexibility suits small businesses and large enterprises alike. Paired with VBA for automation, it empowers users to create custom solutions, making it an indispensable tool for driving insights and optimizing business strategies.
No requirements.
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Excel enables data analysis through tools like PivotTables (summarizing trends), What-If Analysis (scenario modeling), and built-in functions (SUMIFS, XLOOKUP). By organizing datasets into structured tables, users can filter, sort, and visualize data via charts/dashboards. Advanced techniques include forecasting with moving averages and leveraging Power Query to merge/transform data from multiple sources. These capabilities support decision-making by identifying cost-saving opportunities, revenue trends, and operational inefficiencies, making Excel indispensable for business analytics without requiring coding expertise.
Data cleaning involves removing duplicates (Data > Remove Duplicates), fixing errors (IFERROR), and standardizing formats (TEXT, DATEVALUE). Use Power Query to split columns, handle missing values (fill/replace), and unpivot datasets. Functions like TRIM (whitespace removal) and PROPER (text formatting) ensure consistency. Data validation (e.g., drop-down lists) prevents invalid entries. Clean data reduces errors in downstream analysis, ensuring accurate insights for reporting or modeling.
Conditional formatting highlights outliers, trends, or thresholds (e.g., color scales for sales performance). Key functions include VLOOKUP/INDEX-MATCH (data retrieval), SUMIFS/COUNTIFS (conditional aggregations), and TEXTJOIN (combining values). Dynamic arrays (FILTER, SORT) automate data manipulation. Structured references in Excel Tables improve readability. Combining these tools with named ranges and keyboard shortcuts streamlines workflows, enabling quick, repeatable analysis.
Use the Analysis ToolPak for descriptive statistics (mean, median), regression, and t-tests. Functions like CORREL (correlation), FREQUENCY (distribution), and FORECAST.LINEAR (predictions) support statistical analysis. Histograms and scatter plots visualize relationships. Pair PivotTables with GETPIVOTDATA to drill into trends. For A/B testing, calculate confidence intervals using CONFIDENCE.T. These methods transform raw data into actionable insights, such as identifying customer segments or optimizing pricing strategies.