DP-203: Data Engineering on Microsoft Azure

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Introduction

1. How to keep using Azure Portal for FREE after 12 months?
5m

Design Azure Data Storage Solutions (40-45%)

1. SECTION 1 - Introduction and overview
4m

Recommend an Azure data storage solution based on requirements

1. Learning Objectives
2m
2. Data Types
12m
3. Data Storage Types
18m
4. Select Azure Store for application
4m
5. Azure Data Platform Architecture
6m
6. Design and Troubleshoot Partition Distribution type
6m
7. Learning Outcome and Checklist
3m

Design non-relational cloud data stores

1. Learning Objectives
3m
2. What is partitioning and partition key
6m
3. Dedicated vs Shared throughput
7m
4. Avoiding hot partition
5m
5. Single partition vs Cross partition
4m
6. Composite Key
3m
7. Partition key best practice
8m
8. Globally Distribution
13m
9. Multi Master
9m
10. Manual vs Automatics Failover
8m
11. Throughput and request units
9m
12. Cosmos DB - 5 consistent levels
14m
13. Cosmos DB Multi Model 5 APIs
12m
14. How Data Lake Gen 2 Evolved?
5m
15. Data Lake vs Blob
5m
16. High Availability vs Disaster Recovery
7m
17. RTO and RPO
4m
18. Azure Storage - HA and DR Options
12m
19. Cosmos DB - HA and DR Options
17m
20. Scenarios - Designing a solution for CosmosDB vs Data Lake vs Blob Storage
10m
21. Learning Outcome and Checklist
3m

Design relational cloud data stores

1. Learning Objectives
4m
2. Purchasing models and Service Tier
13m
3. Storage and Sharding patterns
5m
4. Data Distribution and Distributing Keys
6m
5. Data Types and Table Types
5m
6. Partitioning
5m
7. Scaling Azure Database
11m
8. Scaling Azure Datawarehouse
3m
9. Azure SQL Database High Availability and Disaster Recovery options
29m
10. Azure SQL Database Backup and Restore
19m
11. Azure SQL Datawarehouse Backup and Restore
11m
12. Azure SQL Database vs Data Warehouse
3m
13. Scenarios - Designing for SQL Database vs Data warehouse
6m
14. Learning Outcome and Checklist
6m

Design Data Processing Solutions (25-30%)

1. SECTION 2 - Introduction and Overview
3m

Design batch processing solutions

1. Learning Objectives
4m
2. Design Batch Processing Solutions using Data Factory and DataBricks
17m
3. Data Ingestion Methods
13m
4. Tools to Ingest Data
11m
5. Ingest using Portal and SE
9m
6. Demo: Ingest Data using azcopy
6m
7. Demo: Blob to Gen 2
9m
8. Demo: SQL Server to Gen2
14m
9. Demo: Amazon S3 to Gen2
8m
10. Learning Outcome and Checklist
3m

Design real-time processing solutions

1. Learning Objectives
2m
2. Real Time Processing
12m
3. Azure Streaming Analytics Service
6m
4. Streaming Analytics - What is time windowing
2m
5. Tumbling Window
3m
6. Hopping Window
2m
7. Sliding Window
2m
8. Session Window
6m
9. Design and Provision Compute Resources
9m
10. Lambda Architecture
10m
11. Learning Outcome and Checklist
4m

Design for Data Security and Compliance (25-30%)

1. SECTION 3 - Introduction and Overview
2m

Design security for source data access

1. Learning Objectives
2m
2. Plan for Secure Endpoints (Public/Private)
7m
3. Access Keys
3m
4. Shared Access Signature (SAS)
7m
5. Active Directory (Azure AD)
5m
6. Role Based Access Control (RBAC)
6m
7. Learning Outcome and Checklist
2m

Design security for data policies and standards

1. Learning Objectives
2m
2. Encrypt data at rest and in transit
26m
3. Data Auditing
4m
4. Data Masking
21m
5. Data Privacy and Data Classification
7m
6. Data Retention and Archiving Strategy
14m
7. Learning Outcome and Checklist
4m