DP-203 Microsoft Azure Data Engineer Associate Exam Prep

LU1 Get started with data engineering on Azure

Topic 1 Introduction to data engineering on Azure

• What is data engineering
• Important data engineering concepts
• Data engineering in Microsoft Azure

Topic 2 Introduction to Azure Data Lake Storage Gen2

• Understand Azure Data Lake Storage Gen
• Enable Azure Data Lake Storage Gen2 in Azure Storage
• Compare Azure Data Lake Store to Azure Blob storage
• Understand the stages for processing big data
• Use Azure Data Lake Storage Gen2 in data analytics workloads

Topic 3 Introduction to Azure Synapse Analytics

• What is Azure Synapse Analytics
• How Azure Synapse Analytics works
• When to use Azure Synapse Analytics
• Exercise - Explore Azure Synapse Analytics

LU2 Build data analytics solutions using Azure Synapse serverless SQL pools

Topic 4 Use Azure Synapse serverless SQL pool to query files in a data lake

• Understand Azure Synapse serverless SQL pool capabilities and use cases
• Query files using a serverless SQL pool
• Create external database objects
• Exercise - Query files using a serverless SQL pool

Topic 5 Use Azure Synapse serverless SQL pools to transform data in a data lake

• Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement
• Encapsulate data transformations in a stored procedure
• Include a data transformation stored procedure in a pipeline
• Exercise - Transform files using a serverless SQL pool

Topic 6 Create a lake database in Azure Synapse Analytics

• Understand lake database concepts
• Explore database templates
• Create a lake database
• Use a lake database
• Exercise - Analyze data in a lake database

Topic 7 Secure data and manage users in Azure Synapse serverless SQL pools

• Choose an authentication method in Azure Synapse serverless SQL pools
• Manage users in Azure Synapse serverless SQL pools
• Manage user permissions in Azure Synapse serverless SQL pools

LU3 Perform data engineering with Azure Synapse Apache Spark Pools

Topic 8 Analyze data with Apache Spark in Azure Synapse Analytics

• Get to know Apache Spark
• Use Spark in Azure Synapse Analytics
• Analyze data with Spark
• Visualize data with Spark
• Exercise - Analyze data with Spark

Topic 9 Transform data with Spark in Azure Synapse Analytics

• Modify and save dataframes
• Partition data files
• Transform data with SQL
• Exercise: Transform data with Spark in Azure Synapse Analytics

Topic 10 Use Delta Lake in Azure Synapse Analytics

• Understand Delta Lake
• Create Delta Lake tables
• Create catalog tables
• Use Delta Lake with streaming data
• Use Delta Lake in a SQL pool
• Exercise - Use Delta Lake in Azure Synapse Analytics

LU4 Work with Data Warehouses using Azure Synapse Analytics

Topic 11 Analyze data in a relational data warehouse

1. Design a data warehouse schema
2. Create data warehouse tables
3. Load data warehouse tables
4. Query a data warehouse
5. Exercise - Explore a data warehouse

Topic 12 Load data into a relational data warehouse

• Load staging tables
• Load dimension tables
• Load time dimension tables
• Load slowly changing dimensions
• Load fact tables
• Perform post load optimization
• Exercise - load data into a relational data warehouse

Topic 13 Manage and monitor data warehouse activities in Azure Synapse Analytics

• Scale compute resources in Azure Synapse Analytics
• Pause compute in Azure Synapse Analytics
• Manage workloads in Azure Synapse Analytics
• Use Azure Advisor to review recommendations
• Use dynamic management views to identify and troubleshoot query performance

Topic 14 Secure a data warehouse in Azure Synapse Analytics

• Understand network security options for Azure Synapse Analytics
• Configure Conditional Access
• Configure authentication
• Manage authorization through column and row level security
• Exercise - Manage authorization through column and row level security
• Manage sensitive data with Dynamic Data Masking
• Implement encryption in Azure Synapse Analytics

LU5 Transfer and transform data with Azure Synapse Analytics pipelines

Topic 15 Build a data pipeline in Azure Synapse Analytics

• Understand pipelines in Azure Synapse Analytics
• Create a pipeline in Azure Synapse Studio
• Define data flows
• Run a pipeline
• Exercise - Build a data pipeline in Azure Synapse Analytics

Topic 16 Use Spark Notebooks in an Azure Synapse Pipeline

• Understand Synapse Notebooks and Pipelines
• Use a Synapse notebook activity in a pipeline
• Use parameters in a notebook
• Exercise - Use an Apache Spark notebook in a pipeline

LU6 Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics

Topic 17 Plan hybrid transactional and analytical processing using Azure Synapse Analytics

• Understand hybrid transactional and analytical processing patterns
• Describe Azure Synapse Link

Topic 18 Implement Azure Synapse Link with Azure Cosmos DB

• Enable Cosmos DB account to use Azure Synapse Link
• Create an analytical store enabled container
• Create a linked service for Cosmos DB
• Query Cosmos DB data with Spark
• Query Cosmos DB with Synapse SQL
• Exercise - Implement Azure Synapse Link for Cosmos DB

Topic 19 Implement Azure Synapse Link for SQL

• What is Azure Synapse Link for SQL?
• Configure Azure Synapse Link for Azure SQL Database
• Configure Azure Synapse Link for SQL Server
• Exercise - Implement Azure Synapse Link for SQL

LU7 Implement a Data Streaming Solution with Azure Stream Analytics

Topic 20 Get started with Azure Stream Analytics

• Understand data streams
• Understand event processing
• Understand window functions
• Exercise - Get started with Azure Stream Analytics

Topic 21 Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics

• Stream ingestion scenarios
• Configure inputs and outputs
• Define a query to select, filter, and aggregate data
• Run a job to ingest data
• Exercise - Ingest streaming data into Azure Synapse Analytics

Topic 22 Visualize real-time data with Azure Stream Analytics and Power BI

• Use a Power BI output in Azure Stream Analytics
• Create a query for real-time visualization
• Create real-time data visualizations in Power BI
• Exercise - Create a real-time data visualization

LU8 Govern data across an enterprise

Topic 23 Introduction to Microsoft Purview

• What is Microsoft Purview?
• How Microsoft Purview works
• When to use Microsoft Purview

Topic 24 Discover trusted data using Microsoft Purview

• Search for assets
• Browse assets
• Use assets with Power BI
• Integrate with Azure Synapse Analytics

Topic 25 Catalog data artifacts by using Microsoft Purview

• Register and scan data
• Classify and label data
• Search the data catalog

Topic 26 Manage Power BI assets by using Microsoft Purview

• Register and scan a Power BI tenant
• Search and browse Power BI assets
• View Power BI metadata and lineage

Topic 27 Integrate Microsoft Purview and Azure Synapse Analytics

• Catalog Azure Synapse Analytics data assets in Microsoft Purview
• Connect Microsoft Purview to an Azure Synapse Analytics workspace
• Search a Purview catalog in Synapse Studio
• Track data lineage in pipelines
• Exercise - Integrate Azure Synapse Analytics and Microsoft Purview

LU9 Data engineering with Azure Databricks

Topic 28 Explore Azure Databricks

• Get started with Azure Databricks
• Identify Azure Databricks workloads
• Understand key concepts
• Exercise - Explore Azure Databricks

Topic 29 Use Apache Spark in Azure Databricks

• Get to know Spark
• Create a Spark cluster
• Use Spark in notebooks
• Use Spark to work with data files
• Visualize data
• Exercise - Use Spark in Azure Databricks

Topic 30 Use Delta Lake in Azure Databricks

• Get Started with Delta Lake
• Create Delta Lake tables
• Create and query catalog tables
• Use Delta Lake for streaming data
• Exercise - Use Delta Lake in Azure Databricks

Topic 31 Use SQL Warehouses in Azure Databricks

• Get started with SQL Warehouses
• Create databases and tables
• Create queries and dashboards
• Exercise - Use a SQL Warehouse in Azure Databricks

Topic 32 Run Azure Databricks Notebooks with Azure Data Factory

• Understand Azure Databricks notebooks and pipelines
• Create a linked service for Azure Databricks
• Use a Notebook activity in a pipeline
• Use parameters in a notebook
• Exercise - Run an Azure Databricks Notebook with Azure Data Factory

Practice Exam

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Minimum Entry Requirement

Knowledge and Skills

• Able to operate using computer functions
• Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)

Attitude

• Positive Learning Attitude
• Enthusiastic Learner

Experience

• Minimum of 1 year of working experience.

Target Age Group: 18-65 years old

Minimum Software/Hardware Requirement

Software:

• R https://cran.r-project.org/
• R Studio https://www.rstudio.com/products/rstudio/download/

Hardware: Window or Mac Laptops

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Dr Alvin Ang: Dr Alvin Ang is a ACTA certified trainer. Dr. Alvin Ang did his Ph.D., Masters and Bachelors from NTU, Singapore. Previously he was a Principal Consultant (Data Science) as well as an Assistant Professor. He was also 8 years SUSS adjunct lecturer. His focus and interest is in the area of real world data science. Though an operational researcher by study, his passion for practical applications outweigh his academic background. He owns a startup externally.

Dwight Nuwan Fonseka: Dwight Nuwan Fonseka is a ACTA certified trainer. Dwight Nuwan Fonseka have a degree in Biotechnology (from NUS), Advanced diploma in Pharmaceutical management (from MDIS) and Masters in Education (from NTU). He have 8 years experience of teaching biology at O and A levels/ IB level in international schools in Singapore and overseas.