DP-203: Data Engineering on Microsoft Azure

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Get ready for your exam by enrolling in our comprehensive training course. This course includes a full set of instructional videos designed to equip you with in-depth knowledge essential for passing the certification exam with flying colors.

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Video Courses

Introduction

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

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

Design Azure Data Storage Solutions (40-45%)

Lectures	Duration
1. SECTION 1 - Introduction and overview	4m

1. SECTION 1 - Introduction and overview

Recommend an Azure data storage solution based on requirements

Lectures	Duration
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

1. Learning Objectives

2. Data Types

12m

3. Data Storage Types

18m

4. Select Azure Store for application

5. Azure Data Platform Architecture

6. Design and Troubleshoot Partition Distribution type

7. Learning Outcome and Checklist

Design non-relational cloud data stores

Lectures	Duration
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

1. Learning Objectives

2. What is partitioning and partition key

3. Dedicated vs Shared throughput

4. Avoiding hot partition

5. Single partition vs Cross partition

6. Composite Key

7. Partition key best practice

8. Globally Distribution

13m

9. Multi Master

10. Manual vs Automatics Failover

11. Throughput and request units

12. Cosmos DB - 5 consistent levels

14m

13. Cosmos DB Multi Model 5 APIs

12m

14. How Data Lake Gen 2 Evolved?

15. Data Lake vs Blob

16. High Availability vs Disaster Recovery

17. RTO and RPO

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

Design relational cloud data stores

Lectures	Duration
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

1. Learning Objectives

2. Purchasing models and Service Tier

13m

3. Storage and Sharding patterns

4. Data Distribution and Distributing Keys

5. Data Types and Table Types

6. Partitioning

7. Scaling Azure Database

11m

8. Scaling Azure Datawarehouse

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

13. Scenarios - Designing for SQL Database vs Data warehouse

14. Learning Outcome and Checklist

Design Data Processing Solutions (25-30%)

Lectures	Duration
1. SECTION 2 - Introduction and Overview	3m

1. SECTION 2 - Introduction and Overview

Design batch processing solutions

Lectures	Duration
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

1. Learning Objectives

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

6. Demo: Ingest Data using azcopy

7. Demo: Blob to Gen 2

8. Demo: SQL Server to Gen2

14m

9. Demo: Amazon S3 to Gen2

10. Learning Outcome and Checklist

Design real-time processing solutions

Lectures	Duration
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

1. Learning Objectives

2. Real Time Processing

12m

3. Azure Streaming Analytics Service

4. Streaming Analytics - What is time windowing

5. Tumbling Window

6. Hopping Window

7. Sliding Window

8. Session Window

9. Design and Provision Compute Resources

10. Lambda Architecture

10m

11. Learning Outcome and Checklist

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

Lectures	Duration
1. SECTION 3 - Introduction and Overview	2m

1. SECTION 3 - Introduction and Overview

Design security for source data access

Lectures	Duration
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

1. Learning Objectives

2. Plan for Secure Endpoints (Public/Private)

3. Access Keys

4. Shared Access Signature (SAS)

5. Active Directory (Azure AD)

6. Role Based Access Control (RBAC)

7. Learning Outcome and Checklist

Design security for data policies and standards

Lectures	Duration
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

1. Learning Objectives

2. Encrypt data at rest and in transit

26m

3. Data Auditing

4. Data Masking

21m

5. Data Privacy and Data Classification

6. Data Retention and Archiving Strategy

14m

7. Learning Outcome and Checklist