Microsoft DP-203 Certification Video Training Course

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DP-203: Data Engineering on Microsoft Azure Certification Video Training Course Outline

25m

Introduction

6 lectures

1h 52m

Design and implement data storag...

17 lectures

34m

Design and implement data storag...

12 lectures

4h 42m

Design and implement data storag...

53 lectures

4h 23m

Design and Develop Data Processi...

36 lectures

2h 58m

Design and Develop Data Processi...

27 lectures

1h 59m

Design and Develop Data Processi...

30 lectures

2h 27m

Design and Develop Data Processi...

34 lectures

1h 49m

Design and Implement Data Security

20 lectures

2h 11m

Monitor and optimize data storag...

27 lectures

Introduction

1. IMPORTANT - How we are going to approach the exam objectives

3:00

2. OPTIONAL - Overview of Azure

2:00

3. OPTIONAL - Concepts in Azure

4:00

4. Azure Free Account

5:00

5. Creating an Azure Free Account

5:00

6. OPTIONAL - Quick tour of the Azure Portal

6:00

1. Section Introduction

2:00

2. Understanding data

4:00

3. Example of data storage

2:00

4. Lab - Azure Storage accounts

6:00

5. Lab - Azure SQL databases

15:00

6. A quick note when it comes to the Azure Free Account

4:00

7. Lab - Application connecting to Azure Storage and SQL database

11:00

8. Different file formats

7:00

9. Azure Data Lake Gen-2 storage accounts

3:00

10. Lab - Creating an Azure Data Lake Gen-2 storage account

9:00

11. Using PowerBI to view your data

7:00

12. Lab - Authorizing to Azure Data Lake Gen 2 - Access Keys - Storage Explorer

6:00

13. Lab - Authorizing to Azure Data Lake Gen 2 - Shared Access Signatures

8:00

14. Azure Storage Account - Redundancy

11:00

15. Azure Storage Account - Access tiers

9:00

16. Azure Storage Account - Lifecycle policy

3:00

17. Note on Costing

5:00

1. Section Introduction

2:00

2. The internals of a database engine

4:00

3. Lab - Setting up a new Azure SQL database

3:00

4. Lab - T-SQL - SELECT clause

3:00

5. Lab - T-SQL - WHERE clause

3:00

6. Lab - T-SQL - ORDER BY clause

1:00

7. Lab - T-SQL - Aggregate Functions

1:00

8. Lab - T-SQL - GROUP BY clause

4:00

9. Lab - T-SQL - HAVING clause

1:00

10. Quick Review on Primary and Foreign Keys

4:00

11. Lab - T-SQL - Creating Tables with Keys

3:00

12. Lab - T-SQL - Table Joins

5:00

1. Section Introduction

2:00

2. Why do we need a data warehouse

10:00

3. Welcome to Azure Synapse Analytics

2:00

4. Lab - Let's create a Azure Synapse workspace

3:00

5. Azure Synapse - Compute options

3:00

6. Using External tables

4:00

7. Lab - Using External tables - Part 1

9:00

8. Lab - Using External tables - Part 2

12:00

9. Lab - Creating a SQL pool

7:00

10. Lab - SQL Pool - External Tables - CSV

9:00

11. Data Cleansing

4:00

12. Lab - SQL Pool - External Tables - CSV with formatted data

3:00

13. Lab - SQL Pool - External Tables - Parquet - Part 1

4:00

14. Lab - SQL Pool - External Tables - Parquet - Part 2

7:00

15. Loading data into the Dedicated SQL Pool

2:00

16. Lab - Loading data into a table - COPY Command - CSV

11:00

17. Lab - Loading data into a table - COPY Command - Parquet

3:00

18. Pausing the Dedicated SQL pool

3:00

19. Lab - Loading data using PolyBase

5:00

20. Lab - BULK INSERT from Azure Synapse

6:00

21. My own experience

6:00

22. Designing a data warehouse

11:00

23. More on dimension tables

5:00

24. Lab - Building a data warehouse - Setting up the database

6:00

25. Lab - Building a Fact Table

8:00

26. Lab - Building a dimension table

6:00

27. Lab - Transfer data to our SQL Pool

15:00

28. Other points in the copy activity

2:00

29. Lab - Using Power BI for Star Schema

6:00

30. Understanding Azure Synapse Architecture

7:00

31. Understanding table types

7:00

32. Understanding Round-Robin tables

5:00

33. Lab - Creating Hash-distributed Tables

5:00

34. Note on creating replicated tables

1:00

35. Designing your tables

4:00

36. Designing tables - Review

4:00

37. Lab - Example when using the right distributions for your tables

10:00

38. Points on tables in Azure Synapse

2:00

39. Lab - Windowing Functions

4:00

40. Lab - Reading JSON files

5:00

41. Lab - Surrogate keys for dimension tables

6:00

42. Slowly Changing dimensions

4:00

43. Type 3 Slowly Dimension dimension

2:00

44. Creating a heap table

3:00

45. Snowflake schema

1:00

46. Lab - CASE statement

6:00

47. Partitions in Azure Synapse

2:00

48. Lab - Creating a table with partitions

11:00

49. Lab - Switching partitions

7:00

50. Indexes

6:00

51. Quick Note - Modern Data Warehouse Architecture

2:00

52. Quick Note on what we are taking forward to the next sections

2:00

53. What about the Spark Pool

2:00

1. Section Introduction

1:00

2. Extract, Transform and Load

2:00

3. What is Azure Data Factory

5:00

4. Starting with Azure Data Factory

2:00

5. Lab - Azure Data Lake to Azure Synapse - Log.csv file

13:00

6. Lab - Azure Data Lake to Azure Synapse - Parquet files

13:00

7. Lab - The case with escape characters

8:00

8. Review on what has been done so far

6:00

9. Lab - Generating a Parquet file

5:00

10. Lab - What about using a query for data transfer

6:00

11. Deleting artefacts in Azure Data Factory

3:00

12. Mapping Data Flow

5:00

13. Lab - Mapping Data Flow - Fact Table

14:00

14. Lab - Mapping Data Flow - Dimension Table - DimCustomer

15:00

15. Lab - Mapping Data Flow - Dimension Table - DimProduct

10:00

16. Lab - Surrogate Keys - Dimension tables

4:00

17. Lab - Using Cache sink

9:00

18. Lab - Handling Duplicate rows

8:00

19. Note - What happens if we don't have any data in our DimProduct table

4:00

20. Changing connection details

1:00

21. Lab - Changing the Time column data in our Log.csv file

8:00

22. Lab - Convert Parquet to JSON

5:00

23. Lab - Loading JSON into SQL Pool

5:00

24. Self-Hosted Integration Runtime

3:00

25. Lab - Self-Hosted Runtime - Setting up nginx

9:00

26. Lab - Self-Hosted Runtime - Setting up the runtime

7:00

27. Lab - Self-Hosted Runtime - Copy Activity

7:00

28. Lab - Self-Hosted Runtime - Mapping Data Flow

16:00

29. Lab - Processing JSON Arrays

8:00

30. Lab - Processing JSON Objects

6:00

31. Lab - Conditional Split

6:00

32. Lab - Schema Drift

12:00

33. Lab - Metadata activity

14:00

34. Lab - Azure DevOps - Git configuration

11:00

35. Lab - Azure DevOps - Release configuration

11:00

36. What resources are we taking forward

1:00

1. Batch and Real-Time Processing

5:00

2. What are Azure Event Hubs

5:00

3. Lab - Creating an instance of Event hub

7:00

4. Lab - Sending and Receiving Events

10:00

5. What is Azure Stream Analytics

2:00

6. Lab - Creating a Stream Analytics job

4:00

7. Lab - Azure Stream Analytics - Defining the job

10:00

8. Review on what we have seen so far

8:00

9. Lab - Reading database diagnostic data - Setup

4:00

10. Lab - Reading data from a JSON file - Setup

6:00

11. Lab - Reading data from a JSON file - Implementation

5:00

12. Lab - Reading data from the Event Hub - Setup

7:00

13. Lab - Reading data from the Event Hub - Implementation

8:00

14. Lab - Timing windows

10:00

15. Lab - Adding multiple outputs

4:00

16. Lab - Reference data

5:00

17. Lab - OVER clause

8:00

18. Lab - Power BI Output

10:00

19. Lab - Reading Network Security Group Logs - Server Setup

3:00

20. Lab - Reading Network Security Group Logs - Enabling NSG Flow Logs

8:00

21. Lab - Reading Network Security Group Logs - Processing the data

13:00

22. Lab - User Defined Functions

9:00

23. Custom Serialization Formats

3:00

24. Lab - Azure Event Hubs - Capture Feature

7:00

25. Lab - Azure Data Factory - Incremental Data Copy

11:00

26. Demo on Azure IoT Devkit

5:00

27. What resources are we taking forward

1:00

1. Section Introduction

2:00

2. Introduction to Scala

2:00

3. Installing Scala

6:00

4. Scala - Playing with values

3:00

5. Scala - Installing IntelliJ IDE

5:00

6. Scala - If construct

3:00

7. Scala - for construct

1:00

8. Scala - while construct

1:00

9. Scala - case construct

1:00

10. Scala - Functions

2:00

11. Scala - List collection

4:00

12. Starting with Python

3:00

13. Python - A simple program

2:00

14. Python - If construct

1:00

15. Python - while construct

1:00

16. Python - List collection

2:00

17. Python - Functions

2:00

18. Quick look at Jupyter Notebook

4:00

19. Lab - Azure Synapse - Creating a Spark pool

8:00

20. Lab - Spark Pool - Starting out with Notebooks

9:00

21. Lab - Spark Pool - Spark DataFrames

4:00

22. Lab - Spark Pool - Sorting data

6:00

23. Lab - Spark Pool - Load data

8:00

24. Lab - Spark Pool - Removing NULL values

8:00

25. Lab - Spark Pool - Using SQL statements

3:00

26. Lab - Spark Pool - Write data to Azure Synapse

11:00

27. Spark Pool - Combined Power

2:00

28. Lab - Spark Pool - Sharing tables

4:00

29. Lab - Spark Pool - Creating tables

5:00

30. Lab - Spark Pool - JSON files

6:00

1. What is Azure Databricks

4:00

2. Clusters in Azure Databricks

6:00

3. Lab - Creating a workspace

3:00

4. Lab - Creating a cluster

14:00

5. Lab - Simple notebook

3:00

6. Lab - Using DataFrames

4:00

7. Lab - Reading a CSV file

4:00

8. Databricks File System

2:00

9. Lab - The SQL Data Frame

3:00

10. Visualizations

1:00

11. Lab - Few functions on dates

2:00

12. Lab - Filtering on NULL values

2:00

13. Lab - Parquet-based files

2:00

14. Lab - JSON-based files

3:00

15. Lab - Structured Streaming - Let's first understand our data

3:00

16. Lab - Structured Streaming - Streaming from Azure Event Hubs - Initial steps

8:00

17. Lab - Structured Streaming - Streaming from Azure Event Hubs - Implementation

10:00

18. Lab - Getting data from Azure Data Lake - Setup

7:00

19. Lab - Getting data from Azure Data Lake - Implementation

5:00

20. Lab - Writing data to Azure Synapse SQL Dedicated Pool

5:00

21. Lab - Stream and write to Azure Synapse SQL Dedicated Pool

5:00

22. Lab - Azure Data Lake Storage Credential Passthrough

10:00

23. Lab - Running an automated job

6:00

24. Autoscaling a cluster

2:00

25. Lab - Removing duplicate rows

3:00

26. Lab - Using the PIVOT command

4:00

27. Lab - Azure Databricks Table

5:00

28. Lab - Azure Data Factory - Running a notebook

6:00

29. Delta Lake Introduction

2:00

30. Lab - Creating a Delta Table

5:00

31. Lab - Streaming data into the table

3:00

32. Lab - Time Travel

2:00

33. Quick note on the deciding between Azure Synapse and Azure Databricks

2:00

34. What resources are we taking forward

1:00

1. Section Introduction

1:00

2. What is the Azure Key Vault service

5:00

3. Azure Data Factory - Encryption

5:00

4. Azure Synapse - Customer Managed Keys

3:00

5. Azure Dedicated SQL Pool - Transparent Data Encryption

2:00

6. Lab - Azure Synapse - Data Masking

10:00

7. Lab - Azure Synapse - Auditing

6:00

8. Azure Synapse - Data Discovery and Classification

4:00

9. Azure Synapse - Azure AD Authentication

3:00

10. Lab - Azure Synapse - Azure AD Authentication - Setting the admin

4:00

11. Lab - Azure Synapse - Azure AD Authentication - Creating a user

8:00

12. Lab - Azure Synapse - Row-Level Security

7:00

13. Lab - Azure Synapse - Column-Level Security

4:00

14. Lab - Azure Data Lake - Role Based Access Control

7:00

15. Lab - Azure Data Lake - Access Control Lists

7:00

16. Lab - Azure Synapse - External Tables Authorization via Managed Identity

8:00

17. Lab - Azure Synapse - External Tables Authorization via Azure AD Authentication

5:00

18. Lab - Azure Synapse - Firewall

7:00

19. Lab - Azure Data Lake - Virtual Network Service Endpoint

7:00

20. Lab - Azure Data Lake - Managed Identity - Data Factory

6:00

1. Best practices for structing files in your data lake

3:00

2. Azure Storage accounts - Query acceleration

2:00

3. View on Azure Monitor

7:00

4. Azure Monitor - Alerts

8:00

5. Azure Synapse - System Views

2:00

6. Azure Synapse - Result set caching

6:00

7. Azure Synapse - Workload Management

4:00

8. Azure Synapse - Retention points

2:00

9. Lab - Azure Data Factory - Monitoring

7:00

10. Azure Data Factory - Monitoring - Alerts and Metrics

4:00

11. Lab - Azure Data Factory - Annotations

3:00

12. Azure Data Factory - Integration Runtime - Note

7:00

13. Azure Data Factory - Pipeline Failures

3:00

14. Azure Key Vault - High Availability

2:00

15. Azure Stream Analytics - Metrics

3:00

16. Azure Stream Analytics - Streaming Units

2:00

17. Azure Stream Analytics - An example on monitoring the stream analytics job

11:00

18. Azure Stream Analytics - The importance of time

7:00

19. Azure Stream Analytics - More on the time aspect

6:00

20. Azure Event Hubs and Stream Analytics - Partitions

5:00

21. Azure Stream Analytics - An example on multiple partitions

7:00

22. Azure Stream Analytics - More on partitions

4:00

23. Azure Stream Analytics - An example on diagnosing errors

4:00

24. Azure Stream Analytics - Diagnostics setting

6:00

25. Azure Databricks - Monitoring

7:00

26. Azure Databricks - Sending logs to Azure Monitor

3:00

27. Azure Event Hubs - High Availability

6:00

DP-203: Data Engineering on Microsoft Azure Certification Video Training Course Info

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