AWS Certified Data Analytics – Specialty

Course Description

The AWS Certified Data Analytics – Specialty certification is designed for professionals who want to demonstrate their deep knowledge of data analytics and data lake architectures on AWS. It validates your ability to build, secure, maintain, and optimize analytics solutions that deliver business insights using AWS services.

This certification goes beyond the basics, focusing on AWS-native tools such as Amazon Redshift, Kinesis, Athena, Glue, Quicksight, and Lake Formation. It prepares candidates to work with both real-time and batch data processing, data visualization, and big data architecture patterns within AWS.

Certification Overview

Credential: AWS Certified Data Analytics – Specialty
Exam Code: DAS-C01
Level: Specialty
Delivery: Pearson VUE or PSI (online or in-person)
Format:

• 65 multiple-choice and multiple-response questions

• Duration: 180 minutes

• Passing score: ~70% (not officially disclosed)

Recommended Experience:

• 5+ years of experience with data analytics technologies

• 2+ years hands-on experience with AWS data analytics services

• Understanding of data storage, processing, visualization, and security

Who This Certification is For

• Data Engineers and Architects working in cloud environments

• Professionals designing or maintaining big data analytics solutions

• AWS users looking to specialize in data-driven decision-making

• BI Developers, ETL Specialists, and Cloud Data Analysts

• Those pursuing a senior-level certification to validate real-world AWS analytics skills

What You’ll Learn / Be Assessed On

1. Data Collection

• Using Amazon Kinesis for real-time streaming ingestion

• Integrating with Amazon S3, DynamoDB, and IoT Core

• Batch ingestion and data movement strategies

2. Data Storage and Management

• Designing scalable data lakes with AWS Lake Formation

• Managing metadata and governance with Glue Catalog

• Choosing the right storage solution (S3, Redshift, RDS, etc.)

3. Data Processing

• ETL/ELT pipelines with AWS Glue and EMR (Spark, Hive, Presto)

• Serverless querying with Amazon Athena

• Real-time processing with Kinesis Data Analytics and Lambda

4. Data Analysis and Visualization

• Business intelligence with Amazon QuickSight

• Performing ad-hoc queries and interactive dashboards

• Integration with third-party tools (Tableau, Power BI, etc.)

5. Security

• Implementing data encryption, IAM, and VPC controls

• Managing permissions, access logging, and key rotation

• Ensuring compliance with data privacy regulations

Tools & Services Covered

• Amazon S3, Redshift, Athena, EMR, Glue

• AWS Lake Formation, Kinesis (Data Streams, Firehose, Analytics)

• QuickSight, Lambda, IAM, CloudWatch

• AWS Data Pipeline, DataBrew, RDS (for comparison)

Skills Validated

• End-to-end data analytics architecture on AWS

• Real-time and batch data processing

• Securing and optimizing data lakes

• Automating and orchestrating ETL workflows

• Delivering insights through interactive dashboards and reports

Course Outcomes

• Earn the AWS Certified Data Analytics – Specialty credential

• Gain recognition as a skilled cloud analytics professional

• Qualify for roles like Senior Data Engineer, Cloud Analytics Architect, or AWS Data Specialist

• Prepare for designing robust, secure, and scalable data analytics platforms on AWS