AWS Certified Data Analytics Specialty (DAS-C01) Training

Description:

This course prepares participants for the AWS Certified Data Analytics – Specialty (DAS-C01) exam by covering all key domains. It equips learners with the knowledge to design, implement, and maintain data analytics solutions using AWS services. Participants will explore topics such as data collection, storage, processing, analysis, and visualization.

The course emphasizes practical application, with hands-on labs and real-world scenarios to ensure participants are well-prepared to leverage AWS services for end-to-end data analytics workflows and succeed in the certification exam.

For Certification based Assistance and Mock quizzes please visit: https://certify360.ai/

Duration: 3 Days

Course Code: BDT419

Learning Objectives:

After completing this course, participants will be able to:

• Understand the key domains of the AWS Certified Data Analytics Specialty exam.
• Design and manage scalable data lakes on AWS.
• Implement data collection, ingestion, and storage solutions.
• Process data with AWS analytics tools like Glue, EMR, and Kinesis.
• Analyse data using Amazon Redshift and Quick Sight.
• Ensure security, governance, and compliance in analytics workflows

• Foundational knowledge of AWS services
• Experience with data analytics workflows and tools
• Familiarity with databases and big data technologies.

• Business Professionals, Data Analysts, Software Developers, IT Managers, Data Engineers, Data Scientist, Solutions Architects, Professionals preparing for the AWS Certified Data Analytics – Specialty exam.

Course Outline:

• Introduction to AWS Data Analytics
  • Overview of AWS Certified Data Analytics Specialty Exam
    1. Exam domains and objectives
    2. Study resources and tips.
  • AWS Data Analytics Services Overview
    1. Key services: S3, Glue, EMR, Redshift, Quick Sight, Kinesis
  • Setting Up the AWS Environment
    1. AWS CLI, SDKs, and IAM configuration

• Data Collection and Ingestion
  • Data Collection Methods
    1. Batch vs. real-time data collection
    2. Tools: Kinesis Data Streams, Kinesis Data Firehose.
  • Data Ingestion Best Practices
    1. Configuring data pipelines for scalability and reliability
    2. Handling diverse data sources.

• Data Storage and Processing
  • Data Storage Solutions on AWS
    1. S3 as a data lake
    2. Glacier for archival storage

• DynamoDB and RDS for structured data.

• Data Processing with AWS Tools
  1. AWS Glue: ETL processes
  2. Amazon EMR: Big data processing with Spark and Hadoop

• Lambda for serverless data processing

• Data Analysis and Visualization
  • Analyzing Data with Amazon Redshift
    1. Configuring Redshift clusters
    2. Query optimization and Redshift Spectrum
  • Data Visualization with Amazon Quick Sight
    1. Creating dashboards and reports
    2. Using machine learning insights in QuickSight.
  • Advanced Analysis Techniques
    1. Integration with third-party tools like Tableau and Power BI

• Security, Governance, and Exam Preparation
  • Securing Analytics Workflows
    1. Encryption, access control, and monitoring with AWS KMS, IAM, and CloudWatch.
  • Data Governance and Compliance
    1. Managing metadata with Glue Data Catalog
    2. Ensuring compliance with regulatory requirements.

• Certification Preparation
  • Certification Tips
    1. Time management and preparation strategies.
    2. Focus areas for success.

• Simulated exams for hands-on experience.

1. Common mistakes and how to avoid them.
2. Key Topics and Objectives for Certification exams.

• Q&A Session
  1. Practice and Mock Tests

Training material provided: Yes (Digital format, including detailed notes, domain-specific study guides, and practice questions).

Any Additional Information

Participants will have access to AWS lab environments for hands-on practice. They are encouraged to have an active AWS account and basic knowledge of analytics workflows. Setup instructions will be provided before the course.

This course ensures participants are prepared for the certification exam and equips them with the practical skills needed for real-world data analytics solutions on AWS.