DP-203: Data Engineering on Microsoft Azure
Your Microsoft DP-203 exam is just around the corner, right? So, it's high time to find an effective preparation tool! Our training course is what you really need! This is a series of videos led by the experienced IT instructors who will provide you with a detailed overview of the DP-203 certification test. Ace your Microsoft DP-203 at the first attempt and obtain the Data Engineering on Microsoft Azure credential with ease.
Curriculum for DP-203 Video Course
Introduction
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
Video Name | Time | |
---|---|---|
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 |
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