The Certified Data Analytics–Specialty is a top-tier expert certification in the AWS data analytics field, focusing on enterprise-level complex data analytics solutions.

1. Introduction to the DAS-C01 certification

AWS Certified Data Analytics Specialty (DAS-C01) is a top-level expert certification in the field of data analytics within the AWS certification system. It focuses on verifying the end-to-end practical ability of practitioners to design, build, automate, and operate enterprise level complex data analytics solutions based on AWS services. It is the "gold standard" for measuring the core competencies of AWS data analytics experts.

In the data-driven transformation of enterprises, it is necessary to transform massive heterogeneous data into decision making business insights, and solve complex problems such as "data lake construction, real-time offline analysis, large-scale data processing, and visualization presentation."

The core of DAS-C01 certification is to cultivate "enterprise level data analytics architects and solution experts in the AWS ecosystem." Not just a user of data tools, but someone who can design analytics solutions that cover the entire process of "data collection storage processing analysis visualization" from business needs, solving core challenges such as data volume explosion, high real-time requirements, and multi scenario analysis, and providing data support for enterprise decision-making.

When designing a comprehensive data analytics solution for retail enterprises, DAS-C01 certification holders will build a "lake warehouse integration" architecture, collect real-time transaction data through Kinesis, calculate real-time indicators through Kinesis Data Analytics, and finally use QuickSight to build a global visualization dashboard. At the same time, data permissions and compliance control will be configured to support decision-making in multiple departments.

2. The Competitive Edge of DAS-C01 Certification

DAS-C01 is the only official AWS data analytics expert certification, with a very low proportion of global holders, making it a "must-have" for companies to recruit "senior data analytics engineers." When recruiting for large companies and AWS partners, they are often listed as the core screening criteria, which is the core indicator to distinguish intermediate and advanced data talents.

DAS-C01 certification focuses on "enterprise level complex scenarios," and passing it can prove the ability to independently solve the core pain points of data analytics, directly lead enterprise level data analytics projects, and become a technical core backbone.

Holders of DAS-C01 certification can join the AWS Global Data Analytics community to access official enterprise level analytics cases and technical whitepapers; priority participation in high-end events such as AWS re:Invent Data Session and Technology Summit, connecting with experts in the same field and opportunities for high-end projects, providing broad career development opportunities.

3. Core Components of the DAS-C01 Certification

For professionals who are committed to becoming data experts and responsible for designing and building enterprise level data analysis and insight platforms, AWS Certified Data Analytics Specialty (DAS-C01) certification is valuable proof of professional competence.

AWS Certified Data Analytics—Specialty certification focuses deeply on end-to-end lifecycle management of modern data analytics pipelines, aiming to systematically verify whether you have the complete technical architecture capabilities to handle data collection, storage, processing, visualization, and security governance.

As the starting point of the data value chain, data collection and ingestion require proficiency in both real-time and offline data ingestion modes. This includes using Kinesis to process high-speed streaming data, as well as implementing batch data migration and database change capture through tools such as DMS and DataSync, ensuring that data can be fully and timely imported into the cloud.

The core of data storage and management lies in selecting appropriate storage solutions based on the needs of data analysis. You need to master the construction and management of data lakes based on S3, deploy high-performance data warehouses using Redshift, and flexibly choose RDS and DynamoDB for transaction, caching, and other scenarios, while utilizing Lake Formation to achieve fine-grained data lake governance.

Data processing and conversion are the core and difficulty of authentication. You will learn to use Glue ETL for large-scale batch processing, utilize Kinesis Data Analytics for real-time stream processing, and use tools such as Glue DataBrew to ensure data quality, transforming raw data into reliable datasets for analysis.

The data query and analysis module focuses on mining the value of data. You need to master the use of Athena for ad hoc queries on data lakes, optimize Redshift to support complex multidimensional analysis, and seamlessly integrate processed data with machine learning services such as SageMaker for predictive analysis.

Finally, certification requires you to have the ability to continuously optimize and ensure system stability. You need to be able to perform performance tuning and cost control on data processing and query tasks, and quickly locate and resolve faults in various links of the data pipeline.

In summary, obtaining DAS-C01 certification not only demonstrates your expert level capabilities in modern data analysis platforms, but also signifies that you have become an indispensable core technical force in enterprise data-driven decision-making.

4. What are the requirements to be an AWS Certified Data Analytics – Specialty?

(1) Qualification prerequisites:

There is no mandatory pre-certification for the DAS-C01 exam, but AWS recommends that you first pass the AWS Cloud Practitioner or DEA-C01 certification to strengthen your AWS foundation and data engineering skills.

We recommend that you have at least 2 years of experience in data analytics and be familiar with core concepts such as data lakes and data warehouses. At the same time, it is recommended that you have at least 1 year of experience using AWS data services and be proficient in S3 and Glue core services; Have basic SQL programming skills, understand Python/Spark basics, and be familiar with data processing and analysis logic. 

(2) Training and examinations:

DAS-C01 consists of approximately 65 questions, including multiple-choice questions and situational analysis questions. The exam lasts for 180 minutes. Full score of 1000, passed with 750 points or above. The exam fee is $300. 

(3) Qualification maintenance:

The DAS-C01 certificate is valid for 3 years, and you need to pass the "renewal exam" or obtain other AWS expert level certifications within the validity period to renew the certificate's validity.

5. Comparable Certifications to AWS Certified Data Analytics – Specialty Certification

• Google Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate
• Cloudera Certified Professional (CCP) Data Engineer
• SAS Certified Big Data Professional