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

The complete solution to prepare for for your exam with DP-203: Data Engineering on Microsoft Azure certification video training course. The DP-203: Data Engineering on Microsoft Azure certification video training course contains a complete set of videos that will provide you with thorough knowledge to understand the key concepts. Top notch prep including Microsoft Azure DP-203 exam dumps, study guide & practice test questions and answers.

122 Students Enrolled
262 Lectures
10:17:00 Hours

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

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1

Introduction

6 Lectures
Time 00:25:00
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2

Design and implement data storage - Basics

17 Lectures
Time 01:52:00
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3

Design and implement data storage - Overview on Transact-SQL

12 Lectures
Time 00:34:00
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4

Design and implement data storage - Azure Synapse Analytics

53 Lectures
Time 04:42:00
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5

Design and Develop Data Processing - Azure Data Factory

36 Lectures
Time 04:23:00
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6

Design and Develop Data Processing - Azure Event Hubs and Stream Analytics

27 Lectures
Time 02:58:00
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7

Design and Develop Data Processing - Scala, Notebooks and Spark

30 Lectures
Time 01:59:00
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8

Design and Develop Data Processing - Azure Databricks

34 Lectures
Time 02:27:00
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9

Design and Implement Data Security

20 Lectures
Time 01:49:00
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10

Monitor and optimize data storage and data processing

27 Lectures
Time 02:11:00

Introduction

  • play 1. IMPORTANT - How we are going to approach the exam objectives
    3:00
  • play 2. OPTIONAL - Overview of Azure
    2:00
  • play 3. OPTIONAL - Concepts in Azure
    4:00
  • play 4. Azure Free Account
    5:00
  • play 5. Creating an Azure Free Account
    5:00
  • play 6. OPTIONAL - Quick tour of the Azure Portal
    6:00

Design and implement data storage - Basics

  • play 1. Section Introduction
    2:00
  • play 2. Understanding data
    4:00
  • play 3. Example of data storage
    2:00
  • play 4. Lab - Azure Storage accounts
    6:00
  • play 5. Lab - Azure SQL databases
    15:00
  • play 6. A quick note when it comes to the Azure Free Account
    4:00
  • play 7. Lab - Application connecting to Azure Storage and SQL database
    11:00
  • play 8. Different file formats
    7:00
  • play 9. Azure Data Lake Gen-2 storage accounts
    3:00
  • play 10. Lab - Creating an Azure Data Lake Gen-2 storage account
    9:00
  • play 11. Using PowerBI to view your data
    7:00
  • play 12. Lab - Authorizing to Azure Data Lake Gen 2 - Access Keys - Storage Explorer
    6:00
  • play 13. Lab - Authorizing to Azure Data Lake Gen 2 - Shared Access Signatures
    8:00
  • play 14. Azure Storage Account - Redundancy
    11:00
  • play 15. Azure Storage Account - Access tiers
    9:00
  • play 16. Azure Storage Account - Lifecycle policy
    3:00
  • play 17. Note on Costing
    5:00

Design and implement data storage - Overview on Transact-SQL

  • play 1. Section Introduction
    2:00
  • play 2. The internals of a database engine
    4:00
  • play 3. Lab - Setting up a new Azure SQL database
    3:00
  • play 4. Lab - T-SQL - SELECT clause
    3:00
  • play 5. Lab - T-SQL - WHERE clause
    3:00
  • play 6. Lab - T-SQL - ORDER BY clause
    1:00
  • play 7. Lab - T-SQL - Aggregate Functions
    1:00
  • play 8. Lab - T-SQL - GROUP BY clause
    4:00
  • play 9. Lab - T-SQL - HAVING clause
    1:00
  • play 10. Quick Review on Primary and Foreign Keys
    4:00
  • play 11. Lab - T-SQL - Creating Tables with Keys
    3:00
  • play 12. Lab - T-SQL - Table Joins
    5:00

Design and implement data storage - Azure Synapse Analytics

  • play 1. Section Introduction
    2:00
  • play 2. Why do we need a data warehouse
    10:00
  • play 3. Welcome to Azure Synapse Analytics
    2:00
  • play 4. Lab - Let's create a Azure Synapse workspace
    3:00
  • play 5. Azure Synapse - Compute options
    3:00
  • play 6. Using External tables
    4:00
  • play 7. Lab - Using External tables - Part 1
    9:00
  • play 8. Lab - Using External tables - Part 2
    12:00
  • play 9. Lab - Creating a SQL pool
    7:00
  • play 10. Lab - SQL Pool - External Tables - CSV
    9:00
  • play 11. Data Cleansing
    4:00
  • play 12. Lab - SQL Pool - External Tables - CSV with formatted data
    3:00
  • play 13. Lab - SQL Pool - External Tables - Parquet - Part 1
    4:00
  • play 14. Lab - SQL Pool - External Tables - Parquet - Part 2
    7:00
  • play 15. Loading data into the Dedicated SQL Pool
    2:00
  • play 16. Lab - Loading data into a table - COPY Command - CSV
    11:00
  • play 17. Lab - Loading data into a table - COPY Command - Parquet
    3:00
  • play 18. Pausing the Dedicated SQL pool
    3:00
  • play 19. Lab - Loading data using PolyBase
    5:00
  • play 20. Lab - BULK INSERT from Azure Synapse
    6:00
  • play 21. My own experience
    6:00
  • play 22. Designing a data warehouse
    11:00
  • play 23. More on dimension tables
    5:00
  • play 24. Lab - Building a data warehouse - Setting up the database
    6:00
  • play 25. Lab - Building a Fact Table
    8:00
  • play 26. Lab - Building a dimension table
    6:00
  • play 27. Lab - Transfer data to our SQL Pool
    15:00
  • play 28. Other points in the copy activity
    2:00
  • play 29. Lab - Using Power BI for Star Schema
    6:00
  • play 30. Understanding Azure Synapse Architecture
    7:00
  • play 31. Understanding table types
    7:00
  • play 32. Understanding Round-Robin tables
    5:00
  • play 33. Lab - Creating Hash-distributed Tables
    5:00
  • play 34. Note on creating replicated tables
    1:00
  • play 35. Designing your tables
    4:00
  • play 36. Designing tables - Review
    4:00
  • play 37. Lab - Example when using the right distributions for your tables
    10:00
  • play 38. Points on tables in Azure Synapse
    2:00
  • play 39. Lab - Windowing Functions
    4:00
  • play 40. Lab - Reading JSON files
    5:00
  • play 41. Lab - Surrogate keys for dimension tables
    6:00
  • play 42. Slowly Changing dimensions
    4:00
  • play 43. Type 3 Slowly Dimension dimension
    2:00
  • play 44. Creating a heap table
    3:00
  • play 45. Snowflake schema
    1:00
  • play 46. Lab - CASE statement
    6:00
  • play 47. Partitions in Azure Synapse
    2:00
  • play 48. Lab - Creating a table with partitions
    11:00
  • play 49. Lab - Switching partitions
    7:00
  • play 50. Indexes
    6:00
  • play 51. Quick Note - Modern Data Warehouse Architecture
    2:00
  • play 52. Quick Note on what we are taking forward to the next sections
    2:00
  • play 53. What about the Spark Pool
    2:00

Design and Develop Data Processing - Azure Data Factory

  • play 1. Section Introduction
    1:00
  • play 2. Extract, Transform and Load
    2:00
  • play 3. What is Azure Data Factory
    5:00
  • play 4. Starting with Azure Data Factory
    2:00
  • play 5. Lab - Azure Data Lake to Azure Synapse - Log.csv file
    13:00
  • play 6. Lab - Azure Data Lake to Azure Synapse - Parquet files
    13:00
  • play 7. Lab - The case with escape characters
    8:00
  • play 8. Review on what has been done so far
    6:00
  • play 9. Lab - Generating a Parquet file
    5:00
  • play 10. Lab - What about using a query for data transfer
    6:00
  • play 11. Deleting artefacts in Azure Data Factory
    3:00
  • play 12. Mapping Data Flow
    5:00
  • play 13. Lab - Mapping Data Flow - Fact Table
    14:00
  • play 14. Lab - Mapping Data Flow - Dimension Table - DimCustomer
    15:00
  • play 15. Lab - Mapping Data Flow - Dimension Table - DimProduct
    10:00
  • play 16. Lab - Surrogate Keys - Dimension tables
    4:00
  • play 17. Lab - Using Cache sink
    9:00
  • play 18. Lab - Handling Duplicate rows
    8:00
  • play 19. Note - What happens if we don't have any data in our DimProduct table
    4:00
  • play 20. Changing connection details
    1:00
  • play 21. Lab - Changing the Time column data in our Log.csv file
    8:00
  • play 22. Lab - Convert Parquet to JSON
    5:00
  • play 23. Lab - Loading JSON into SQL Pool
    5:00
  • play 24. Self-Hosted Integration Runtime
    3:00
  • play 25. Lab - Self-Hosted Runtime - Setting up nginx
    9:00
  • play 26. Lab - Self-Hosted Runtime - Setting up the runtime
    7:00
  • play 27. Lab - Self-Hosted Runtime - Copy Activity
    7:00
  • play 28. Lab - Self-Hosted Runtime - Mapping Data Flow
    16:00
  • play 29. Lab - Processing JSON Arrays
    8:00
  • play 30. Lab - Processing JSON Objects
    6:00
  • play 31. Lab - Conditional Split
    6:00
  • play 32. Lab - Schema Drift
    12:00
  • play 33. Lab - Metadata activity
    14:00
  • play 34. Lab - Azure DevOps - Git configuration
    11:00
  • play 35. Lab - Azure DevOps - Release configuration
    11:00
  • play 36. What resources are we taking forward
    1:00

Design and Develop Data Processing - Azure Event Hubs and Stream Analytics

  • play 1. Batch and Real-Time Processing
    5:00
  • play 2. What are Azure Event Hubs
    5:00
  • play 3. Lab - Creating an instance of Event hub
    7:00
  • play 4. Lab - Sending and Receiving Events
    10:00
  • play 5. What is Azure Stream Analytics
    2:00
  • play 6. Lab - Creating a Stream Analytics job
    4:00
  • play 7. Lab - Azure Stream Analytics - Defining the job
    10:00
  • play 8. Review on what we have seen so far
    8:00
  • play 9. Lab - Reading database diagnostic data - Setup
    4:00
  • play 10. Lab - Reading data from a JSON file - Setup
    6:00
  • play 11. Lab - Reading data from a JSON file - Implementation
    5:00
  • play 12. Lab - Reading data from the Event Hub - Setup
    7:00
  • play 13. Lab - Reading data from the Event Hub - Implementation
    8:00
  • play 14. Lab - Timing windows
    10:00
  • play 15. Lab - Adding multiple outputs
    4:00
  • play 16. Lab - Reference data
    5:00
  • play 17. Lab - OVER clause
    8:00
  • play 18. Lab - Power BI Output
    10:00
  • play 19. Lab - Reading Network Security Group Logs - Server Setup
    3:00
  • play 20. Lab - Reading Network Security Group Logs - Enabling NSG Flow Logs
    8:00
  • play 21. Lab - Reading Network Security Group Logs - Processing the data
    13:00
  • play 22. Lab - User Defined Functions
    9:00
  • play 23. Custom Serialization Formats
    3:00
  • play 24. Lab - Azure Event Hubs - Capture Feature
    7:00
  • play 25. Lab - Azure Data Factory - Incremental Data Copy
    11:00
  • play 26. Demo on Azure IoT Devkit
    5:00
  • play 27. What resources are we taking forward
    1:00

Design and Develop Data Processing - Scala, Notebooks and Spark

  • play 1. Section Introduction
    2:00
  • play 2. Introduction to Scala
    2:00
  • play 3. Installing Scala
    6:00
  • play 4. Scala - Playing with values
    3:00
  • play 5. Scala - Installing IntelliJ IDE
    5:00
  • play 6. Scala - If construct
    3:00
  • play 7. Scala - for construct
    1:00
  • play 8. Scala - while construct
    1:00
  • play 9. Scala - case construct
    1:00
  • play 10. Scala - Functions
    2:00
  • play 11. Scala - List collection
    4:00
  • play 12. Starting with Python
    3:00
  • play 13. Python - A simple program
    2:00
  • play 14. Python - If construct
    1:00
  • play 15. Python - while construct
    1:00
  • play 16. Python - List collection
    2:00
  • play 17. Python - Functions
    2:00
  • play 18. Quick look at Jupyter Notebook
    4:00
  • play 19. Lab - Azure Synapse - Creating a Spark pool
    8:00
  • play 20. Lab - Spark Pool - Starting out with Notebooks
    9:00
  • play 21. Lab - Spark Pool - Spark DataFrames
    4:00
  • play 22. Lab - Spark Pool - Sorting data
    6:00
  • play 23. Lab - Spark Pool - Load data
    8:00
  • play 24. Lab - Spark Pool - Removing NULL values
    8:00
  • play 25. Lab - Spark Pool - Using SQL statements
    3:00
  • play 26. Lab - Spark Pool - Write data to Azure Synapse
    11:00
  • play 27. Spark Pool - Combined Power
    2:00
  • play 28. Lab - Spark Pool - Sharing tables
    4:00
  • play 29. Lab - Spark Pool - Creating tables
    5:00
  • play 30. Lab - Spark Pool - JSON files
    6:00

Design and Develop Data Processing - Azure Databricks

  • play 1. What is Azure Databricks
    4:00
  • play 2. Clusters in Azure Databricks
    6:00
  • play 3. Lab - Creating a workspace
    3:00
  • play 4. Lab - Creating a cluster
    14:00
  • play 5. Lab - Simple notebook
    3:00
  • play 6. Lab - Using DataFrames
    4:00
  • play 7. Lab - Reading a CSV file
    4:00
  • play 8. Databricks File System
    2:00
  • play 9. Lab - The SQL Data Frame
    3:00
  • play 10. Visualizations
    1:00
  • play 11. Lab - Few functions on dates
    2:00
  • play 12. Lab - Filtering on NULL values
    2:00
  • play 13. Lab - Parquet-based files
    2:00
  • play 14. Lab - JSON-based files
    3:00
  • play 15. Lab - Structured Streaming - Let's first understand our data
    3:00
  • play 16. Lab - Structured Streaming - Streaming from Azure Event Hubs - Initial steps
    8:00
  • play 17. Lab - Structured Streaming - Streaming from Azure Event Hubs - Implementation
    10:00
  • play 18. Lab - Getting data from Azure Data Lake - Setup
    7:00
  • play 19. Lab - Getting data from Azure Data Lake - Implementation
    5:00
  • play 20. Lab - Writing data to Azure Synapse SQL Dedicated Pool
    5:00
  • play 21. Lab - Stream and write to Azure Synapse SQL Dedicated Pool
    5:00
  • play 22. Lab - Azure Data Lake Storage Credential Passthrough
    10:00
  • play 23. Lab - Running an automated job
    6:00
  • play 24. Autoscaling a cluster
    2:00
  • play 25. Lab - Removing duplicate rows
    3:00
  • play 26. Lab - Using the PIVOT command
    4:00
  • play 27. Lab - Azure Databricks Table
    5:00
  • play 28. Lab - Azure Data Factory - Running a notebook
    6:00
  • play 29. Delta Lake Introduction
    2:00
  • play 30. Lab - Creating a Delta Table
    5:00
  • play 31. Lab - Streaming data into the table
    3:00
  • play 32. Lab - Time Travel
    2:00
  • play 33. Quick note on the deciding between Azure Synapse and Azure Databricks
    2:00
  • play 34. What resources are we taking forward
    1:00

Design and Implement Data Security

  • play 1. Section Introduction
    1:00
  • play 2. What is the Azure Key Vault service
    5:00
  • play 3. Azure Data Factory - Encryption
    5:00
  • play 4. Azure Synapse - Customer Managed Keys
    3:00
  • play 5. Azure Dedicated SQL Pool - Transparent Data Encryption
    2:00
  • play 6. Lab - Azure Synapse - Data Masking
    10:00
  • play 7. Lab - Azure Synapse - Auditing
    6:00
  • play 8. Azure Synapse - Data Discovery and Classification
    4:00
  • play 9. Azure Synapse - Azure AD Authentication
    3:00
  • play 10. Lab - Azure Synapse - Azure AD Authentication - Setting the admin
    4:00
  • play 11. Lab - Azure Synapse - Azure AD Authentication - Creating a user
    8:00
  • play 12. Lab - Azure Synapse - Row-Level Security
    7:00
  • play 13. Lab - Azure Synapse - Column-Level Security
    4:00
  • play 14. Lab - Azure Data Lake - Role Based Access Control
    7:00
  • play 15. Lab - Azure Data Lake - Access Control Lists
    7:00
  • play 16. Lab - Azure Synapse - External Tables Authorization via Managed Identity
    8:00
  • play 17. Lab - Azure Synapse - External Tables Authorization via Azure AD Authentication
    5:00
  • play 18. Lab - Azure Synapse - Firewall
    7:00
  • play 19. Lab - Azure Data Lake - Virtual Network Service Endpoint
    7:00
  • play 20. Lab - Azure Data Lake - Managed Identity - Data Factory
    6:00

Monitor and optimize data storage and data processing

  • play 1. Best practices for structing files in your data lake
    3:00
  • play 2. Azure Storage accounts - Query acceleration
    2:00
  • play 3. View on Azure Monitor
    7:00
  • play 4. Azure Monitor - Alerts
    8:00
  • play 5. Azure Synapse - System Views
    2:00
  • play 6. Azure Synapse - Result set caching
    6:00
  • play 7. Azure Synapse - Workload Management
    4:00
  • play 8. Azure Synapse - Retention points
    2:00
  • play 9. Lab - Azure Data Factory - Monitoring
    7:00
  • play 10. Azure Data Factory - Monitoring - Alerts and Metrics
    4:00
  • play 11. Lab - Azure Data Factory - Annotations
    3:00
  • play 12. Azure Data Factory - Integration Runtime - Note
    7:00
  • play 13. Azure Data Factory - Pipeline Failures
    3:00
  • play 14. Azure Key Vault - High Availability
    2:00
  • play 15. Azure Stream Analytics - Metrics
    3:00
  • play 16. Azure Stream Analytics - Streaming Units
    2:00
  • play 17. Azure Stream Analytics - An example on monitoring the stream analytics job
    11:00
  • play 18. Azure Stream Analytics - The importance of time
    7:00
  • play 19. Azure Stream Analytics - More on the time aspect
    6:00
  • play 20. Azure Event Hubs and Stream Analytics - Partitions
    5:00
  • play 21. Azure Stream Analytics - An example on multiple partitions
    7:00
  • play 22. Azure Stream Analytics - More on partitions
    4:00
  • play 23. Azure Stream Analytics - An example on diagnosing errors
    4:00
  • play 24. Azure Stream Analytics - Diagnostics setting
    6:00
  • play 25. Azure Databricks - Monitoring
    7:00
  • play 26. Azure Databricks - Sending logs to Azure Monitor
    3:00
  • play 27. Azure Event Hubs - High Availability
    6:00
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About DP-203: Data Engineering on Microsoft Azure Certification Video Training Course

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Prepaway's DP-203: Data Engineering on Microsoft Azure video training course for passing certification exams is the only solution which you need.

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  • Training Course 262 Video Lectures
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