Training Video Course

DP-203: Data Engineering on Microsoft Azure

PDFs and exam guides are not so efficient, right? Prepare for your Microsoft examination with our training course. The DP-203 course contains a complete batch of videos that will provide you with profound and thorough knowledge related to Microsoft certification exam. Pass the Microsoft DP-203 test with flying colors.

Rating
4.44rating
Students
100
Duration
10:17:00 h
$16.49
$14.99

Curriculum for DP-203 Certification Video Course

Name of Video Time
Play Video: IMPORTANT - How we are going to approach the exam objectives
1. IMPORTANT - How we are going to approach the exam objectives
3:00
Play Video: OPTIONAL - Overview of Azure
2. OPTIONAL - Overview of Azure
2:00
Play Video: OPTIONAL - Concepts in Azure
3. OPTIONAL - Concepts in Azure
4:00
Play Video: Azure Free Account
4. Azure Free Account
5:00
Play Video: Creating an Azure Free Account
5. Creating an Azure Free Account
5:00
Play Video: OPTIONAL - Quick tour of the Azure Portal
6. OPTIONAL - Quick tour of the Azure Portal
6:00
Name of Video Time
Play Video: Section Introduction
1. Section Introduction
2:00
Play Video: Understanding data
2. Understanding data
4:00
Play Video: Example of data storage
3. Example of data storage
2:00
Play Video: Lab - Azure Storage accounts
4. Lab - Azure Storage accounts
6:00
Play Video: Lab - Azure SQL databases
5. Lab - Azure SQL databases
15:00
Play Video: A quick note when it comes to the Azure Free Account
6. A quick note when it comes to the Azure Free Account
4:00
Play Video: Lab - Application connecting to Azure Storage and SQL database
7. Lab - Application connecting to Azure Storage and SQL database
11:00
Play Video: Different file formats
8. Different file formats
7:00
Play Video: Azure Data Lake Gen-2 storage accounts
9. Azure Data Lake Gen-2 storage accounts
3:00
Play Video: Lab - Creating an Azure Data Lake Gen-2 storage account
10. Lab - Creating an Azure Data Lake Gen-2 storage account
9:00
Play Video: Using PowerBI to view your data
11. Using PowerBI to view your data
7:00
Play Video: Lab - Authorizing to Azure Data Lake Gen 2 - Access Keys - Storage Explorer
12. Lab - Authorizing to Azure Data Lake Gen 2 - Access Keys - Storage Explorer
6:00
Play Video: Lab - Authorizing to Azure Data Lake Gen 2 - Shared Access Signatures
13. Lab - Authorizing to Azure Data Lake Gen 2 - Shared Access Signatures
8:00
Play Video: Azure Storage Account - Redundancy
14. Azure Storage Account - Redundancy
11:00
Play Video: Azure Storage Account - Access tiers
15. Azure Storage Account - Access tiers
9:00
Play Video: Azure Storage Account - Lifecycle policy
16. Azure Storage Account - Lifecycle policy
3:00
Play Video: Note on Costing
17. Note on Costing
5:00
Name of Video Time
Play Video: Section Introduction
1. Section Introduction
2:00
Play Video: The internals of a database engine
2. The internals of a database engine
4:00
Play Video: Lab - Setting up a new Azure SQL database
3. Lab - Setting up a new Azure SQL database
3:00
Play Video: Lab - T-SQL - SELECT clause
4. Lab - T-SQL - SELECT clause
3:00
Play Video: Lab - T-SQL - WHERE clause
5. Lab - T-SQL - WHERE clause
3:00
Play Video: Lab - T-SQL - ORDER BY clause
6. Lab - T-SQL - ORDER BY clause
1:00
Play Video: Lab - T-SQL - Aggregate Functions
7. Lab - T-SQL - Aggregate Functions
1:00
Play Video: Lab - T-SQL - GROUP BY clause
8. Lab - T-SQL - GROUP BY clause
4:00
Play Video: Lab - T-SQL - HAVING clause
9. Lab - T-SQL - HAVING clause
1:00
Play Video: Quick Review on Primary and Foreign Keys
10. Quick Review on Primary and Foreign Keys
4:00
Play Video: Lab - T-SQL - Creating Tables with Keys
11. Lab - T-SQL - Creating Tables with Keys
3:00
Play Video: Lab - T-SQL - Table Joins
12. Lab - T-SQL - Table Joins
5:00
Name of Video Time
Play Video: Section Introduction
1. Section Introduction
2:00
Play Video: Why do we need a data warehouse
2. Why do we need a data warehouse
10:00
Play Video: Welcome to Azure Synapse Analytics
3. Welcome to Azure Synapse Analytics
2:00
Play Video: Lab - Let's create a Azure Synapse workspace
4. Lab - Let's create a Azure Synapse workspace
3:00
Play Video: Azure Synapse - Compute options
5. Azure Synapse - Compute options
3:00
Play Video: Using External tables
6. Using External tables
4:00
Play Video: Lab - Using External tables - Part 1
7. Lab - Using External tables - Part 1
9:00
Play Video: Lab - Using External tables - Part 2
8. Lab - Using External tables - Part 2
12:00
Play Video: Lab - Creating a SQL pool
9. Lab - Creating a SQL pool
7:00
Play Video: Lab - SQL Pool - External Tables - CSV
10. Lab - SQL Pool - External Tables - CSV
9:00
Play Video: Data Cleansing
11. Data Cleansing
4:00
Play Video: Lab - SQL Pool - External Tables - CSV with formatted data
12. Lab - SQL Pool - External Tables - CSV with formatted data
3:00
Play Video: Lab - SQL Pool - External Tables - Parquet - Part 1
13. Lab - SQL Pool - External Tables - Parquet - Part 1
4:00
Play Video: Lab - SQL Pool - External Tables - Parquet - Part 2
14. Lab - SQL Pool - External Tables - Parquet - Part 2
7:00
Play Video: Loading data into the Dedicated SQL Pool
15. Loading data into the Dedicated SQL Pool
2:00
Play Video: Lab - Loading data into a table - COPY Command - CSV
16. Lab - Loading data into a table - COPY Command - CSV
11:00
Play Video: Lab - Loading data into a table - COPY Command - Parquet
17. Lab - Loading data into a table - COPY Command - Parquet
3:00
Play Video: Pausing the Dedicated SQL pool
18. Pausing the Dedicated SQL pool
3:00
Play Video: Lab - Loading data using PolyBase
19. Lab - Loading data using PolyBase
5:00
Play Video: Lab - BULK INSERT from Azure Synapse
20. Lab - BULK INSERT from Azure Synapse
6:00
Play Video: My own experience
21. My own experience
6:00
Play Video: Designing a data warehouse
22. Designing a data warehouse
11:00
Play Video: More on dimension tables
23. More on dimension tables
5:00
Play Video: Lab - Building a data warehouse - Setting up the database
24. Lab - Building a data warehouse - Setting up the database
6:00
Play Video: Lab - Building a Fact Table
25. Lab - Building a Fact Table
8:00
Play Video: Lab - Building a dimension table
26. Lab - Building a dimension table
6:00
Play Video: Lab - Transfer data to our SQL Pool
27. Lab - Transfer data to our SQL Pool
15:00
Play Video: Other points in the copy activity
28. Other points in the copy activity
2:00
Play Video: Lab - Using Power BI for Star Schema
29. Lab - Using Power BI for Star Schema
6:00
Play Video: Understanding Azure Synapse Architecture
30. Understanding Azure Synapse Architecture
7:00
Play Video: Understanding table types
31. Understanding table types
7:00
Play Video: Understanding Round-Robin tables
32. Understanding Round-Robin tables
5:00
Play Video: Lab - Creating Hash-distributed Tables
33. Lab - Creating Hash-distributed Tables
5:00
Play Video: Note on creating replicated tables
34. Note on creating replicated tables
1:00
Play Video: Designing your tables
35. Designing your tables
4:00
Play Video: Designing tables - Review
36. Designing tables - Review
4:00
Play Video: Lab - Example when using the right distributions for your tables
37. Lab - Example when using the right distributions for your tables
10:00
Play Video: Points on tables in Azure Synapse
38. Points on tables in Azure Synapse
2:00
Play Video: Lab - Windowing Functions
39. Lab - Windowing Functions
4:00
Play Video: Lab - Reading JSON files
40. Lab - Reading JSON files
5:00
Play Video: Lab - Surrogate keys for dimension tables
41. Lab - Surrogate keys for dimension tables
6:00
Play Video: Slowly Changing dimensions
42. Slowly Changing dimensions
4:00
Play Video: Type 3 Slowly Dimension dimension
43. Type 3 Slowly Dimension dimension
2:00
Play Video: Creating a heap table
44. Creating a heap table
3:00
Play Video: Snowflake schema
45. Snowflake schema
1:00
Play Video: Lab - CASE statement
46. Lab - CASE statement
6:00
Play Video: Partitions in Azure Synapse
47. Partitions in Azure Synapse
2:00
Play Video: Lab - Creating a table with partitions
48. Lab - Creating a table with partitions
11:00
Play Video: Lab - Switching partitions
49. Lab - Switching partitions
7:00
Play Video: Indexes
50. Indexes
6:00
Play Video: Quick Note - Modern Data Warehouse Architecture
51. Quick Note - Modern Data Warehouse Architecture
2:00
Play Video: Quick Note on what we are taking forward to the next sections
52. Quick Note on what we are taking forward to the next sections
2:00
Play Video: What about the Spark Pool
53. What about the Spark Pool
2:00
Name of Video Time
Play Video: Section Introduction
1. Section Introduction
1:00
Play Video: Extract, Transform and Load
2. Extract, Transform and Load
2:00
Play Video: What is Azure Data Factory
3. What is Azure Data Factory
5:00
Play Video: Starting with Azure Data Factory
4. Starting with Azure Data Factory
2:00
Play Video: Lab - Azure Data Lake to Azure Synapse - Log.csv file
5. Lab - Azure Data Lake to Azure Synapse - Log.csv file
13:00
Play Video: Lab - Azure Data Lake to Azure Synapse - Parquet files
6. Lab - Azure Data Lake to Azure Synapse - Parquet files
13:00
Play Video: Lab - The case with escape characters
7. Lab - The case with escape characters
8:00
Play Video: Review on what has been done so far
8. Review on what has been done so far
6:00
Play Video: Lab - Generating a Parquet file
9. Lab - Generating a Parquet file
5:00
Play Video: Lab - What about using a query for data transfer
10. Lab - What about using a query for data transfer
6:00
Play Video: Deleting artefacts in Azure Data Factory
11. Deleting artefacts in Azure Data Factory
3:00
Play Video: Mapping Data Flow
12. Mapping Data Flow
5:00
Play Video: Lab - Mapping Data Flow - Fact Table
13. Lab - Mapping Data Flow - Fact Table
14:00
Play Video: Lab - Mapping Data Flow - Dimension Table - DimCustomer
14. Lab - Mapping Data Flow - Dimension Table - DimCustomer
15:00
Play Video: Lab - Mapping Data Flow - Dimension Table - DimProduct
15. Lab - Mapping Data Flow - Dimension Table - DimProduct
10:00
Play Video: Lab - Surrogate Keys - Dimension tables
16. Lab - Surrogate Keys - Dimension tables
4:00
Play Video: Lab - Using Cache sink
17. Lab - Using Cache sink
9:00
Play Video: Lab - Handling Duplicate rows
18. Lab - Handling Duplicate rows
8:00
Play Video: Note - What happens if we don't have any data in our DimProduct table
19. Note - What happens if we don't have any data in our DimProduct table
4:00
Play Video: Changing connection details
20. Changing connection details
1:00
Play Video: Lab - Changing the Time column data in our Log.csv file
21. Lab - Changing the Time column data in our Log.csv file
8:00
Play Video: Lab - Convert Parquet to JSON
22. Lab - Convert Parquet to JSON
5:00
Play Video: Lab - Loading JSON into SQL Pool
23. Lab - Loading JSON into SQL Pool
5:00
Play Video: Self-Hosted Integration Runtime
24. Self-Hosted Integration Runtime
3:00
Play Video: Lab - Self-Hosted Runtime - Setting up nginx
25. Lab - Self-Hosted Runtime - Setting up nginx
9:00
Play Video: Lab - Self-Hosted Runtime - Setting up the runtime
26. Lab - Self-Hosted Runtime - Setting up the runtime
7:00
Play Video: Lab - Self-Hosted Runtime - Copy Activity
27. Lab - Self-Hosted Runtime - Copy Activity
7:00
Play Video: Lab - Self-Hosted Runtime - Mapping Data Flow
28. Lab - Self-Hosted Runtime - Mapping Data Flow
16:00
Play Video: Lab - Processing JSON Arrays
29. Lab - Processing JSON Arrays
8:00
Play Video: Lab - Processing JSON Objects
30. Lab - Processing JSON Objects
6:00
Play Video: Lab - Conditional Split
31. Lab - Conditional Split
6:00
Play Video: Lab - Schema Drift
32. Lab - Schema Drift
12:00
Play Video: Lab - Metadata activity
33. Lab - Metadata activity
14:00
Play Video: Lab - Azure DevOps - Git configuration
34. Lab - Azure DevOps - Git configuration
11:00
Play Video: Lab - Azure DevOps - Release configuration
35. Lab - Azure DevOps - Release configuration
11:00
Play Video: What resources are we taking forward
36. What resources are we taking forward
1:00
Name of Video Time
Play Video: Batch and Real-Time Processing
1. Batch and Real-Time Processing
5:00
Play Video: What are Azure Event Hubs
2. What are Azure Event Hubs
5:00
Play Video: Lab - Creating an instance of Event hub
3. Lab - Creating an instance of Event hub
7:00
Play Video: Lab - Sending and Receiving Events
4. Lab - Sending and Receiving Events
10:00
Play Video: What is Azure Stream Analytics
5. What is Azure Stream Analytics
2:00
Play Video: Lab - Creating a Stream Analytics job
6. Lab - Creating a Stream Analytics job
4:00
Play Video: Lab - Azure Stream Analytics - Defining the job
7. Lab - Azure Stream Analytics - Defining the job
10:00
Play Video: Review on what we have seen so far
8. Review on what we have seen so far
8:00
Play Video: Lab - Reading database diagnostic data - Setup
9. Lab - Reading database diagnostic data - Setup
4:00
Play Video: Lab - Reading data from a JSON file - Setup
10. Lab - Reading data from a JSON file - Setup
6:00
Play Video: Lab - Reading data from a JSON file - Implementation
11. Lab - Reading data from a JSON file - Implementation
5:00
Play Video: Lab - Reading data from the Event Hub - Setup
12. Lab - Reading data from the Event Hub - Setup
7:00
Play Video: Lab - Reading data from the Event Hub - Implementation
13. Lab - Reading data from the Event Hub - Implementation
8:00
Play Video: Lab - Timing windows
14. Lab - Timing windows
10:00
Play Video: Lab - Adding multiple outputs
15. Lab - Adding multiple outputs
4:00
Play Video: Lab - Reference data
16. Lab - Reference data
5:00
Play Video: Lab - OVER clause
17. Lab - OVER clause
8:00
Play Video: Lab - Power BI Output
18. Lab - Power BI Output
10:00
Play Video: Lab - Reading Network Security Group Logs - Server Setup
19. Lab - Reading Network Security Group Logs - Server Setup
3:00
Play Video: Lab - Reading Network Security Group Logs - Enabling NSG Flow Logs
20. Lab - Reading Network Security Group Logs - Enabling NSG Flow Logs
8:00
Play Video: Lab - Reading Network Security Group Logs - Processing the data
21. Lab - Reading Network Security Group Logs - Processing the data
13:00
Play Video: Lab - User Defined Functions
22. Lab - User Defined Functions
9:00
Play Video: Custom Serialization Formats
23. Custom Serialization Formats
3:00
Play Video: Lab - Azure Event Hubs - Capture Feature
24. Lab - Azure Event Hubs - Capture Feature
7:00
Play Video: Lab - Azure Data Factory - Incremental Data Copy
25. Lab - Azure Data Factory - Incremental Data Copy
11:00
Play Video: Demo on Azure IoT Devkit
26. Demo on Azure IoT Devkit
5:00
Play Video: What resources are we taking forward
27. What resources are we taking forward
1:00
Name of Video Time
Play Video: Section Introduction
1. Section Introduction
2:00
Play Video: Introduction to Scala
2. Introduction to Scala
2:00
Play Video: Installing Scala
3. Installing Scala
6:00
Play Video: Scala - Playing with values
4. Scala - Playing with values
3:00
Play Video: Scala - Installing IntelliJ IDE
5. Scala - Installing IntelliJ IDE
5:00
Play Video: Scala - If construct
6. Scala - If construct
3:00
Play Video: Scala - for construct
7. Scala - for construct
1:00
Play Video: Scala - while construct
8. Scala - while construct
1:00
Play Video: Scala - case construct
9. Scala - case construct
1:00
Play Video: Scala - Functions
10. Scala - Functions
2:00
Play Video: Scala - List collection
11. Scala - List collection
4:00
Play Video: Starting with Python
12. Starting with Python
3:00
Play Video: Python - A simple program
13. Python - A simple program
2:00
Play Video: Python - If construct
14. Python - If construct
1:00
Play Video: Python - while construct
15. Python - while construct
1:00
Play Video: Python - List collection
16. Python - List collection
2:00
Play Video: Python - Functions
17. Python - Functions
2:00
Play Video: Quick look at Jupyter Notebook
18. Quick look at Jupyter Notebook
4:00
Play Video: Lab - Azure Synapse - Creating a Spark pool
19. Lab - Azure Synapse - Creating a Spark pool
8:00
Play Video: Lab - Spark Pool - Starting out with Notebooks
20. Lab - Spark Pool - Starting out with Notebooks
9:00
Play Video: Lab - Spark Pool - Spark DataFrames
21. Lab - Spark Pool - Spark DataFrames
4:00
Play Video: Lab - Spark Pool - Sorting data
22. Lab - Spark Pool - Sorting data
6:00
Play Video: Lab - Spark Pool - Load data
23. Lab - Spark Pool - Load data
8:00
Play Video: Lab - Spark Pool - Removing NULL values
24. Lab - Spark Pool - Removing NULL values
8:00
Play Video: Lab - Spark Pool - Using SQL statements
25. Lab - Spark Pool - Using SQL statements
3:00
Play Video: Lab - Spark Pool - Write data to Azure Synapse
26. Lab - Spark Pool - Write data to Azure Synapse
11:00
Play Video: Spark Pool - Combined Power
27. Spark Pool - Combined Power
2:00
Play Video: Lab - Spark Pool - Sharing tables
28. Lab - Spark Pool - Sharing tables
4:00
Play Video: Lab - Spark Pool - Creating tables
29. Lab - Spark Pool - Creating tables
5:00
Play Video: Lab - Spark Pool - JSON files
30. Lab - Spark Pool - JSON files
6:00
Name of Video Time
Play Video: What is Azure Databricks
1. What is Azure Databricks
4:00
Play Video: Clusters in Azure Databricks
2. Clusters in Azure Databricks
6:00
Play Video: Lab - Creating a workspace
3. Lab - Creating a workspace
3:00
Play Video: Lab - Creating a cluster
4. Lab - Creating a cluster
14:00
Play Video: Lab - Simple notebook
5. Lab - Simple notebook
3:00
Play Video: Lab - Using DataFrames
6. Lab - Using DataFrames
4:00
Play Video: Lab - Reading a CSV file
7. Lab - Reading a CSV file
4:00
Play Video: Databricks File System
8. Databricks File System
2:00
Play Video: Lab - The SQL Data Frame
9. Lab - The SQL Data Frame
3:00
Play Video: Visualizations
10. Visualizations
1:00
Play Video: Lab - Few functions on dates
11. Lab - Few functions on dates
2:00
Play Video: Lab - Filtering on NULL values
12. Lab - Filtering on NULL values
2:00
Play Video: Lab - Parquet-based files
13. Lab - Parquet-based files
2:00
Play Video: Lab - JSON-based files
14. Lab - JSON-based files
3:00
Play Video: Lab - Structured Streaming - Let's first understand our data
15. Lab - Structured Streaming - Let's first understand our data
3:00
Play Video: Lab - Structured Streaming - Streaming from Azure Event Hubs - Initial steps
16. Lab - Structured Streaming - Streaming from Azure Event Hubs - Initial steps
8:00
Play Video: Lab - Structured Streaming - Streaming from Azure Event Hubs - Implementation
17. Lab - Structured Streaming - Streaming from Azure Event Hubs - Implementation
10:00
Play Video: Lab - Getting data from Azure Data Lake - Setup
18. Lab - Getting data from Azure Data Lake - Setup
7:00
Play Video: Lab - Getting data from Azure Data Lake - Implementation
19. Lab - Getting data from Azure Data Lake - Implementation
5:00
Play Video: Lab - Writing data to Azure Synapse SQL Dedicated Pool
20. Lab - Writing data to Azure Synapse SQL Dedicated Pool
5:00
Play Video: Lab - Stream and write to Azure Synapse SQL Dedicated Pool
21. Lab - Stream and write to Azure Synapse SQL Dedicated Pool
5:00
Play Video: Lab - Azure Data Lake Storage Credential Passthrough
22. Lab - Azure Data Lake Storage Credential Passthrough
10:00
Play Video: Lab - Running an automated job
23. Lab - Running an automated job
6:00
Play Video: Autoscaling a cluster
24. Autoscaling a cluster
2:00
Play Video: Lab - Removing duplicate rows
25. Lab - Removing duplicate rows
3:00
Play Video: Lab - Using the PIVOT command
26. Lab - Using the PIVOT command
4:00
Play Video: Lab - Azure Databricks Table
27. Lab - Azure Databricks Table
5:00
Play Video: Lab - Azure Data Factory - Running a notebook
28. Lab - Azure Data Factory - Running a notebook
6:00
Play Video: Delta Lake Introduction
29. Delta Lake Introduction
2:00
Play Video: Lab - Creating a Delta Table
30. Lab - Creating a Delta Table
5:00
Play Video: Lab - Streaming data into the table
31. Lab - Streaming data into the table
3:00
Play Video: Lab - Time Travel
32. Lab - Time Travel
2:00
Play Video: Quick note on the deciding between Azure Synapse and Azure Databricks
33. Quick note on the deciding between Azure Synapse and Azure Databricks
2:00
Play Video: What resources are we taking forward
34. What resources are we taking forward
1:00
Name of Video Time
Play Video: Section Introduction
1. Section Introduction
1:00
Play Video: What is the Azure Key Vault service
2. What is the Azure Key Vault service
5:00
Play Video: Azure Data Factory - Encryption
3. Azure Data Factory - Encryption
5:00
Play Video: Azure Synapse - Customer Managed Keys
4. Azure Synapse - Customer Managed Keys
3:00
Play Video: Azure Dedicated SQL Pool - Transparent Data Encryption
5. Azure Dedicated SQL Pool - Transparent Data Encryption
2:00
Play Video: Lab - Azure Synapse - Data Masking
6. Lab - Azure Synapse - Data Masking
10:00
Play Video: Lab - Azure Synapse - Auditing
7. Lab - Azure Synapse - Auditing
6:00
Play Video: Azure Synapse - Data Discovery and Classification
8. Azure Synapse - Data Discovery and Classification
4:00
Play Video: Azure Synapse - Azure AD Authentication
9. Azure Synapse - Azure AD Authentication
3:00
Play Video: Lab - Azure Synapse - Azure AD Authentication - Setting the admin
10. Lab - Azure Synapse - Azure AD Authentication - Setting the admin
4:00
Play Video: Lab - Azure Synapse - Azure AD Authentication - Creating a user
11. Lab - Azure Synapse - Azure AD Authentication - Creating a user
8:00
Play Video: Lab - Azure Synapse - Row-Level Security
12. Lab - Azure Synapse - Row-Level Security
7:00
Play Video: Lab - Azure Synapse - Column-Level Security
13. Lab - Azure Synapse - Column-Level Security
4:00
Play Video: Lab - Azure Data Lake - Role Based Access Control
14. Lab - Azure Data Lake - Role Based Access Control
7:00
Play Video: Lab - Azure Data Lake - Access Control Lists
15. Lab - Azure Data Lake - Access Control Lists
7:00
Play Video: Lab - Azure Synapse - External Tables Authorization via Managed Identity
16. Lab - Azure Synapse - External Tables Authorization via Managed Identity
8:00
Play Video: Lab - Azure Synapse - External Tables Authorization via Azure AD Authentication
17. Lab - Azure Synapse - External Tables Authorization via Azure AD Authentication
5:00
Play Video: Lab - Azure Synapse - Firewall
18. Lab - Azure Synapse - Firewall
7:00
Play Video: Lab - Azure Data Lake - Virtual Network Service Endpoint
19. Lab - Azure Data Lake - Virtual Network Service Endpoint
7:00
Play Video: Lab - Azure Data Lake - Managed Identity - Data Factory
20. Lab - Azure Data Lake - Managed Identity - Data Factory
6:00
Name of Video Time
Play Video: Best practices for structing files in your data lake
1. Best practices for structing files in your data lake
3:00
Play Video: Azure Storage accounts - Query acceleration
2. Azure Storage accounts - Query acceleration
2:00
Play Video: View on Azure Monitor
3. View on Azure Monitor
7:00
Play Video: Azure Monitor - Alerts
4. Azure Monitor - Alerts
8:00
Play Video: Azure Synapse - System Views
5. Azure Synapse - System Views
2:00
Play Video: Azure Synapse - Result set caching
6. Azure Synapse - Result set caching
6:00
Play Video: Azure Synapse - Workload Management
7. Azure Synapse - Workload Management
4:00
Play Video: Azure Synapse - Retention points
8. Azure Synapse - Retention points
2:00
Play Video: Lab - Azure Data Factory - Monitoring
9. Lab - Azure Data Factory - Monitoring
7:00
Play Video: Azure Data Factory - Monitoring - Alerts and Metrics
10. Azure Data Factory - Monitoring - Alerts and Metrics
4:00
Play Video: Lab - Azure Data Factory - Annotations
11. Lab - Azure Data Factory - Annotations
3:00
Play Video: Azure Data Factory - Integration Runtime - Note
12. Azure Data Factory - Integration Runtime - Note
7:00
Play Video: Azure Data Factory - Pipeline Failures
13. Azure Data Factory - Pipeline Failures
3:00
Play Video: Azure Key Vault - High Availability
14. Azure Key Vault - High Availability
2:00
Play Video: Azure Stream Analytics - Metrics
15. Azure Stream Analytics - Metrics
3:00
Play Video: Azure Stream Analytics - Streaming Units
16. Azure Stream Analytics - Streaming Units
2:00
Play Video: Azure Stream Analytics - An example on monitoring the stream analytics job
17. Azure Stream Analytics - An example on monitoring the stream analytics job
11:00
Play Video: Azure Stream Analytics - The importance of time
18. Azure Stream Analytics - The importance of time
7:00
Play Video: Azure Stream Analytics - More on the time aspect
19. Azure Stream Analytics - More on the time aspect
6:00
Play Video: Azure Event Hubs and Stream Analytics - Partitions
20. Azure Event Hubs and Stream Analytics - Partitions
5:00
Play Video: Azure Stream Analytics - An example on multiple partitions
21. Azure Stream Analytics - An example on multiple partitions
7:00
Play Video: Azure Stream Analytics - More on partitions
22. Azure Stream Analytics - More on partitions
4:00
Play Video: Azure Stream Analytics - An example on diagnosing errors
23. Azure Stream Analytics - An example on diagnosing errors
4:00
Play Video: Azure Stream Analytics - Diagnostics setting
24. Azure Stream Analytics - Diagnostics setting
6:00
Play Video: Azure Databricks - Monitoring
25. Azure Databricks - Monitoring
7:00
Play Video: Azure Databricks - Sending logs to Azure Monitor
26. Azure Databricks - Sending logs to Azure Monitor
3:00
Play Video: Azure Event Hubs - High Availability
27. Azure Event Hubs - High Availability
6:00

Microsoft Azure DP-203 Exam Dumps, Practice Test Questions

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Microsoft DP-203 Training Course

Want verified and proven knowledge for Data Engineering on Microsoft Azure? Believe it's easy when you have ExamSnap's Data Engineering on Microsoft Azure certification video training course by your side which along with our Microsoft DP-203 Exam Dumps & Practice Test questions provide a complete solution to pass your exam Read More.

Design and implement data storage - Overview on Transact-SQL

6. Lab - T-SQL - ORDER BY clause

Let's go to the next SQL file. So this is the order by clause. Now the order by clause is used to sort the result set in either ascending or descending order. By default, the records are sorted in ascending order. So here I am selecting all the rows from the sales as the product table, but I'm ordering them by the list price. So I'll just replace it over here and hit execute. And I'm seeing everything that is being sorted as per the list price. If you want to list it in descending order, just add the descending keyword over here and hit execute. And now the list price or the rows are being displayed to you based on the descending order of the list price. So in this chapter, I just want to quickly go through the order by clause.

7. Lab - T-SQL - Aggregate Functions

Let's go on to our next sequel file. Now, here I am looking at aggregate functions. Aggregation is now very important when it comes to analysis of your data. So, more often than not, you will actually be performing aggregation of your data. To look at stats about the data itself here, let's say I want to find the number of products. I'm using Product ID over here. When the product name is like Isai, it contains the name of silver. It contains a string of silver. You can go ahead and copy this, and I can execute it over here. So I can see there are three things that actually fulfil this condition. If you want to find the Max Product ID, you can go ahead and execute that as well. So the Max product ID is nine, eight, eight. Similarly, you can also go ahead and find the minimum Product ID and hit Execute so you get the minimum Product ID wherein this condition is being fulfilled. If you want to find the sum, or if you want to find the average, you can go ahead and actually use these Aggregation function. We’ll also be using these aggregate functions in Azure Stream Antics because normally data engineers will use aggregate functions when it comes to their streaming data.

8. Lab - T-SQL - GROUP BY clause

Now let's go on to the next sequel statement. Now this is the group I clause, probably one of the most important clauses. So the group I keyword is used to group the rows into summary rows and this is used normally along with aggregate functions. So over here I want to see the count of the product ID from the sales table and I'm grouping it by the color. So the color column value, if I go ahead and copy this and replace it over here, hit on execute. So here I can see the number of product IDs that are grouped by the color. I can go a step further and give an alias on to the count of the product ID because as you can see over here, there is no column name. So I can take this, copy it over here, and it will execute. So I can see now a name is being given to our column. So product ID counts. I can take it even a step further. I can now see the color as well, so I can see a better representation of my data. I'll hit on execute. So now I can see for the color, let's say black, we have 89 products that match this color. So we can see all of these details. Here you can see that there are products which have no color at all. Null Values: Again, very important when you're working with your data is how do you actually consider rows that have null values. Sometimes you might want to put a default value over there if there is a null value for that particular column. Or you might totally discard the rows that have the null value for a particular column. You might actually consider discarding those rows if they don't give any meaning to the final result set on which you are trying to form an analysis. Performing or giving a default value is also sometimes a risk because it can sometimes skew your data. So you should always think very carefully about your data performance analysis.

What are you going to do for those roles that actually have a null value? So over here, if you only now want to see an account of the products wherein the color is not null, we can go ahead and execute the statement and we're getting the results as desired. Now, when it comes to the group by clause in the SQL data warehouse, again a very important concept. And over there, when you want to increase the efficiency of the group pi cross, you will actually be using different types of tables. So we have hash distributed tables and we also have something known as replicated tables. We also have round robin tables. But when it comes to the group by clause and you are going to see this later on, we are going to be working with something known as fact tables and dimension tables. And normally you use grouping when you are working with your fact and dimension tables, and at that point in time, to have an effective distribution of data, you'll actually create tables, types of tables. So in the SQL data warehouse, you have hash distribute table types and replicated distribution table types. So we will be looking at all of these table types when we are looking at the SQL data warehouse.

9. Lab - T-SQL - HAVING clause

So I'll go on to the next file. So this is just the having clause. So here, the aggregate functions of the sum count cannot be used along with the where clause. So you can actually use it in the possessing clause here. The only difference is that I only want to have a result set wherein the number of products that actually match a particular color is greater than ten. That's it. If I take the statement, if I place it over here and hit execute, we are only getting those rows. Then where the number of products is greater than ten, the count of the products based on a particular color is greater than ten.

10. Quick Review on Primary and Foreign Keys

Now in this chapter, I just want to have a quick review when it comes to primary keys and foreign keys. So, primary keys are used to uniquely identify rows within a particular table. So if you are certain that you don't have duplicate rows in place, you can go in and enforce the primary key constraint on a particular table. This is a feature that is available in most SQL database systems, and then you have the foreign key. So, if you have one table that has a dependency on another table, you can have a foreign key constraint. If I go on to my Object Explorer, when you look at the sample tables that we have over here, I'm sure that there is a relationship between the tables over here.

So if I consider the product, the product category, the description, and the model, I want to see what the relationship between these tables is. If I, for example, go on to the sales table, if I go on to the keys, So here I can see that there is an primary key that is based on the product ID. So this means that the Product ID value is unique for every row. That means you can't have two rows that have the same product ID. I can see that there are also foreign key constraints that are being mapped onto other tables. So there is a relationship between the product table and the product category table, and there is a relationship between the product table and the product model table. If you want to see the visualization of the relationships again, you can actually do it from SQL Server Management Studio. You can right click on database diagrams. You can click on the new database diagram here. It will give you a message that one or more of these support objects required is not in place.

Do you want to create them? I'll click "yes." Then it should give me a screen wherein I can choose which tables I want to add on to my database diagram. So I'll choose my product table, I'll choose my product category table, and my product model table. I'll click on Add, and it will add all of these tables onto my database diagram. Once I have the tables in place, I'll close this. So here you can see that we have an primary key that is defined on the product table.

There is also a primary key on the product category table and a primary key on the product model table. There is also a relationship between the product table and the product category table, and there is a relationship between the product table and the product model table. Here the columns that are actually mapping tables are so we have the product category ID in the product table.

This is actually being mapped onto the product category id column that we have in the product category table. And then we have the Product Model ID column that will be mapped on to the Product Mode lid column in the Product Model table. When it comes to understanding the relationships between tables, this is going to be a very important concept that we will be learning in the sequel data warehouse. So based on relationships, based on the columns, you can actually construct something known as our Dimension Tables, which will be used in something known as the star Schema, and that's something that we're going to look at in detail at this point in time. Just a quick review to keep in mind that you have your primary keys and you have the foreign keys that are used to depict the relationships between the tables.

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