AWS Associate Data Engineer Training Course - India 

Domain 1: Data Ingestion and Transformation

• Perform Data Ingestion

• Throughput and Latency Characteristics for AWS Services that Ingest Data
• Data Ingestion Patterns
• Streaming Data Ingestion
• Batch Data Ingestion
• Replayability of Data Ingestion Pipelines
• Stateful and Stateless Data Transactions

• Transform and Process Data

• Creation of ETL Pipelines Based on Business Requirements
• Volume, Velocity, and Variety of Data
• Cloud Computing and Distributed Computing
• How to Use Apache Spark to Process Data
• Intermediate Data Staging Locations

• Orchestrate Data Pipelines

• How to Integrate Various AWS Services to Create ETL Pipelines
• Event-driven Architecture
• How to Configure AWS Services for Data Pipelines Based on Schedules or Dependencies
• Serverless Workflows

• Apply Programming Concepts

• Continuous Integration and Continuous Delivery
• SQL Queries
• Infrastructure as Code
• Distributed Computing
• Data Structures and Algorithms
• SQL Query Optimisation

Domain 2: Data Store Management

• Choose a Data Store

• Storage Platforms and Their Characteristics
• Storage Services and Configurations for Specific Performance Demands
• Data Storage Formats
• How to Align Data Storage with Data Migration Requirements
• How to Determine the Appropriate Storage Solution for Specific Access Patterns
• How to Manage Locks to Prevent Access to Data

• Understand Data Cataloguing Systems

• How to Create a Data Catalog
• Data Classification Based on Requirements
• Components of Metadata and Data Catalogs

• Manage the Lifecycle of Data

• Appropriate Storage Solutions to Address Hot and Cold Data Requirements
• How to Optimise the Cost of Storage Based on the Data Lifecycle
• How to Delete Data to Meet Business and Legal Requirements
• Data Retention Policies and Archiving Strategies
• How to Protect Data with Appropriate Resiliency and Availability

• Design Data Models and Schema Evolution

• Data Modelling Concepts
• How to Ensure Accuracy and Trustworthiness of Data by Using Data Lineage
• Best Practices for Indexing, Partitioning Strategies, Compression, and Other Data Optimisation Techniques
• How to Model Structured, Semi-structured, and Unstructured Data
• Schema Evolution Techniques

Domain 3: Data Operations and Support

• Automate Data Processing by Using AWS Services

• How to Maintain and Troubleshoot Data Processing for Repeatable Business Outcomes
• API Calls for Data Processing
• Which Services Accept Scripting

• Analyse Data by Using AWS Services

• Tradeoffs Between Provisioned Services and Serverless Services
• SQL Queries
• How to Visualise Data for Analysis
• When and How to Apply Cleansing Techniques
• Data Aggregation, Rolling Average, Grouping, and Pivoting

• Maintain and Monitor Data Pipelines

• How to Log Application Data
• Best Practices for Performance Tuning
• How to Log Access to AWS Services
• Amazon Macie, AWS CloudTrail, and Amazon CloudWatch

• Ensure Data Quality

• Data Sampling Techniques
• How to Implement Data Skew Mechanisms
• Data Validation
• Data Profiling

Domain 4: Data Security and Governance

• Apply Authentication Mechanisms

• VPC Security Networking Concepts
• Differences Between Managed Services and Unmanaged Services
• Authentication Methods
• Differences Between AWS Managed Policies and Customer Managed Policies

• Apply Authorisation Mechanisms

• Authorisation Methods
• Principle of Least Privilege as It Applies to AWS Security
• Role-based Access Control and Expected Access Patterns
• Methods to Protect Data from Unauthorised Access Across Services

• Ensure Data Encryption and Masking

• Data Encryption Options Available in AWS Analytics Services
• Differences Between Client-side Encryption and Server-side Encryption
• Protection of Sensitive Data
• Data Anonymisation, Masking, and Key Salting

• Prepare Logs for Audit

• How to Log Application Data
• How to Log Access to AWS Services
• Centralised AWS Logs

• Understand Data Privacy and Governance.

• How to Protect Personally Identifiable Information
• Data Sovereignty