Data Ingestion + Transformation

Data ingestion patterns (for example, frequency and data history)

Batch data ingestion (for example, scheduled ingestion, event-driven ingestion)

Replayability of data ingestion pipelines

Reading data from batch sources

Implementing appropriate configuration options for batch ingestion

Creation of ETL pipelines based on business requirements

Volume, velocity, and variety of data (e.g., structured data, unstructured data)

Cloud computing and distributed computing

SQL queries (for data source queries and data transformations)

Data modeling concepts

How to model structured, semi-structured, and unstructured data

Schema evolution techniques

Designing schemas for Amazon Redshift, DynamoDB, and Lake Formation

Addressing changes to the characteristics of data

How to maintain and troubleshoot data processing for repeatable business outcomes

Calling SDKs to access Amazon features from code

Preparing data transformation (for example, AWS Glue DataBrew)

Querying data (for example, Amazon Athena)

Tradeoffs between provisioned services and serverless services

SQL queries (for example, SELECT statements with multiple qualifiers or JOIN clauses)

How to visualize data for analysis

When and how to apply cleansing techniques

Data aggregation, rolling average, grouping, and pivoting

Verifying and cleaning data (for example, Lambda, Athena, QuickSight, Jupyter Notebooks, Amazon SageMaker Data Wrangler)

Using Athena to query data or to create views

How to log application data

Amazon Macie, AWS CloudTrail, and Amazon CloudWatch

Extracting logs for audits

Deploying logging and monitoring solutions to facilitate auditing and traceability

Analyzing logs with AWS services (for example, Athena, Amazon EMR, Amazon OpenSearch Service, CloudWatch Logs Insights, big data application logs)

Data Sampling Techniques

How to Implement Data Skew Mechanisms

Data Validation (Data Completeness, Consistency, Accuracy, and Integrity)

Differences Between Managed Services and Unmanaged Services

Principle of Least Privilege (PoLP) as it Applies to AWS Security

Protection of Sensitive Data

Protecting Personally Identifiable Information (PII)

Data Sovereignty

Amazon Athena

AWS Glue

AWS Glue DataBrew

Amazon QuickSight

AWS Budgets

AWS Cost Explorer

Amazon EC2 (Elastic Compute Cloud)

AWS Lambda

Amazon RDS (Relational Database Service)

Amazon Redshift

AWS CodeBuild

AWS CodeCommit

Amazon SageMaker

AWS CloudTrail

Amazon CloudWatch

Amazon CloudWatch Logs

AWS Snow Family

AWS Transfer Family

Amazon Route 53

Amazon VPC (Virtual Private Cloud)

AWS Identity and Access Management (IAM)

AWS Key Management Service (AWS KMS)

Amazon Macie

AWS Secrets Manager

AWS Shield and AWS WAF

AWS Backup

Amazon S3

Amazon S3 Glacier