Microsoft Azure Data Engineer Associate (DP-203) Cert Prep: 1 Design and Implement Data Storage by Microsoft Press

Introduction

• Introduction

1. Design and Implement Data Storage

• Learning objectives
• Design an Azure Data Lake solution
• Recommend file types for storage
• Recommend file types for analytical queries
• Design for efficient querying

2. Design for Data Pruning

• Learning objectives
• Design a folder structure that represents levels of data transformation
• Design a distribution strategy
• Design a data archiving solution

3. Design a Partition Strategy

• Learning objectives
• Design a partition strategy for files
• Design a partition strategy for analytical workloads
• Design a partition strategy for efficiency and performance
• Design a partition strategy for Azure Synapse Analytics
• Identify when partitioning is needed in Azure Data Lake Storage Gen2

4. Design the Serving Layer

• Learning objectives
• Design star schemas
• Design slowly changing dimensions
• Design a dimensional hierarchy
• Design a solution for temporal data
• Design for incremental loading
• Design analytical stores
• Design metastores in Azure Synapse Analytics and Azure Databricks

5. Implement Physical Data Storage Structures

• Learning objectives
• Implement compression
• Implement partitioning
• Implement sharding
• Implement different table geometries with Azure Synapse Analytics pools
• Implement data redundancy
• Implement distributions
• Implement data archiving

6. Implement Logical Data Structures

• Learning objectives
• Build a temporal data solution
• Build a slowly changing dimension
• Build a logical folder structure
• Build external tables
• Implement file and folder structures for efficient querying and data pruning

7. Implement the Serving Layer

• Learning objectives
• Deliver data in a relational star schema
• Deliver data in Parquet files
• Maintain metadata
• Implement a dimensional hierarchy