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

Course details

The latest professional certifications from Azure are aligned with specific industry roles. Earning your Azure certification helps to validate your unique Azure skill set and increase your value in today's IT job market. Join Microsoft MVP and Microsoft Certified Azure Solutions Architect Tim Warner for an overview of the core concepts and skills required to pass the Microsoft Azure Data Engineer Associate (DP-203) certification exam. In this course, the first in a four-part certification prep series, explore the fundamentals of how to design and implement data storage solutions. Ensure that data pipelines and data stores are high performing, efficient, organized, and reliable, given a set of business requirements and constraints specific to your organization. Learn how to deal with unanticipated issues swiftly, minimize data loss, and design, implement, monitor, and optimize data platforms and structures to meet data pipeline needs.

Concepts

0. Introduction

01 - Introduction

1. Design and Implement Data Storage

02 - Learning objectives
03 - Design an Azure Data Lake solution
04 - Recommend file types for storage
05 - Recommend file types for analytical queries
06 - Design for efficient querying

2. Design for Data Pruning

07 - Learning objectives
08 - Design a folder structure that represents levels of data transformation
09 - Design a distribution strategy
10 - Design a data archiving solution

3. Design a Partition Strategy

11 - Learning objectives
12 - Design a partition strategy for files
13 - Design a partition strategy for analytical workloads
14 - Design a partition strategy for efficiency and performance
15 - Design a partition strategy for Azure Synapse Analytics
16 - Identify when partitioning is needed in Azure Data Lake Storage Gen2

4. Design the Serving Layer

17 - Learning objectives
18 - Design star schemas
19 - Design slowly changing dimensions
20 - Design a dimensional hierarchy
21 - Design a solution for temporal data
22 - Design for incremental loading
23 - Design analytical stores
24 - Design metastores in Azure Synapse Analytics and Azure Databricks

5. Implement Physical Data Storage Structures

25 - Learning objectives
26 - Implement compression
27 - Implement partitioning
28 - Implement sharding
29 - Implement different table geometries with Azure Synapse Analytics pools
30 - Implement data redundancy
31 - Implement distributions
32 - Implement data archiving

6. Implement Logical Data Structures

33 - Learning objectives
34 - Build a temporal data solution
35 - Build a slowly changing dimension
36 - Build a logical folder structure
37 - Build external tables
38 - Implement file and folder structures for efficient querying and data pruning

7. Implement the Serving Layer

39 - Learning objectives
40 - Deliver data in a relational star schema
41 - Deliver data in Parquet files
42 - Maintain metadata
43 - Implement a dimensional hierarchy

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

Authors

Microsoft Learn

Tim Warner