DP-3012: Implementing a Data Analytics Solution with Azure Synapse Analytics

The DP-3012 Implementing a Data Analytics Solution with Azure Synapse Analytics course teaches how to design and implement data analytics solutions using Azure Synapse Analytics for large-scale data processing and real-time insights.

Target Audience

• Data Engineer

• Azure Administrator

Prerequisites
Recommended:

• Familiarity with notebooks that use different languages and a Spark engine, such as Databricks, Jupyter Notebooks, Zeppelin notebooks, and more.

• Some experience with SQL, Python, and Azure tools, such as Data Factory.

• AI+ Executive™

• AI+ Prompt Engineer™: Level 1

• DP-900T00: Introduction to Microsoft Azure Data

Course Objectives

• Introduction to Azure Synapse Analytics

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

• Analyze data with Apache Spark in Azure Synapse Analytics

• Use Delta Lake in Azure Synapse Analytics

• Analyze data in a relational data warehouse

• Build a data pipeline in Azure Synapse Analytics

Course Outline

1) Implement a Data Analytics Solution with Azure Synapse Analytics

• Introduction to Azure Synapse Analytics

  • Identify the business problems that Azure Synapse Analytics addresses

  • Describe core capabilities of Azure Synapse Analytics

  • Determine when to use Azure Synapse Analytics

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

  • Identify capabilities and use cases for serverless SQL pools in Azure Synapse Analytics

  • Query CSV, JSON, and Parquet files using a serverless SQL pool

  • Create external database objects in a serverless SQL pool

• Analyze data with Apache Spark in Azure Synapse Analytics

  • Identify core features and capabilities of Apache Spark

  • Configure a Spark pool in Azure Synapse Analytics

  • Run code to load, analyze, and visualize data in a Spark notebook

• Use Delta Lake in Azure Synapse Analytics

  • Describe core features and capabilities of Delta Lake

  • Create and use Delta Lake tables in a Synapse Analytics Spark pool

  • Create Spark catalog tables for Delta Lake data

  • Use Delta Lake tables for streaming data

  • Query Delta Lake tables from a Synapse Analytics SQL pool

• Analyze data in a relational data warehouse

  • Design a schema for a relational data warehouse

  • Create fact, dimension, and staging tables

  • Use SQL to load data into data warehouse tables

  • Use SQL to query relational data warehouse tables

• Build a data pipeline in Azure Synapse Analytics

  • Describe core concepts for Azure Synapse Analytics pipelines

  • Create a pipeline in Azure Synapse Studio

  • Implement a data flow activity in a pipeline

  • Initiate and monitor pipeline runs

2) Build data analytics solutions using Azure Synapse serverless SQL pools

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

  • Identify capabilities and use cases for serverless SQL pools

  • Query CSV, JSON, and Parquet files using a serverless SQL pool

  • Create external database objects in a serverless SQL pool

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

  • Use a CREATE EXTERNAL TABLE AS SELECT (CETAS) statement to transform data

  • Encapsulate a CETAS statement in a stored procedure

  • Include a data transformation stored procedure in a pipeline

• Create a lake database in Azure Synapse Analytics

  • Understand lake database concepts and components

  • Describe database templates in Azure Synapse Analytics

  • Create a lake database

• Secure data and manage users in Azure Synapse serverless SQL pools

  • Choose an authentication method in serverless SQL pools

  • Manage users in serverless SQL pools

  • Manage user permissions in serverless SQL pools

3) Perform data engineering with Azure Synapse Apache Spark Pools

• Analyze data with Apache Spark in Azure Synapse Analytics

  • Identify core features and capabilities of Apache Spark

  • Configure a Spark pool in Azure Synapse Analytics

  • Run code to load, analyze, and visualize data in a Spark notebook

• Transform data with Spark in Azure Synapse Analytics

  • Use Apache Spark to modify and save dataframes

  • Partition data files for improved performance and scalability

  • Transform data with SQL

• Use Delta Lake in Azure Synapse Analytics

  • Describe core features and capabilities of Delta Lake

  • Create and use Delta Lake tables in a Spark pool

  • Create Spark catalog tables for Delta Lake data

  • Use Delta Lake tables for streaming data

  • Query Delta Lake tables from a Synapse Analytics SQL pool

4) Work with Data Warehouses using Azure Synapse Analytics

• Analyze data in a relational data warehouse

  • Design a schema for a relational data warehouse

  • Create fact, dimension, and staging tables

  • Use SQL to load data into data warehouse tables

  • Use SQL to query relational data warehouse tables

• Load data into a relational data warehouse

  • Load staging tables in a data warehouse

  • Load dimension tables in a data warehouse

  • Load time dimensions in a data warehouse

  • Load slowly changing dimensions in a data warehouse

  • Load fact tables in a data warehouse

  • Perform post-load optimizations in a data warehouse

• 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

• 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

  • Manage sensitive data with Dynamic Data Masking

  • Implement encryption in Azure Synapse Analytics

5) Transfer and transform data with Azure Synapse Analytics pipelines

• Build a data pipeline in Azure Synapse Analytics

  • Describe core concepts for Azure Synapse Analytics pipelines

  • Create a pipeline in Azure Synapse Studio

  • Implement a data flow activity in a pipeline

  • Initiate and monitor pipeline runs

• Use Spark Notebooks in an Azure Synapse Pipeline

  • Describe notebook and pipeline integration

  • Use a Synapse notebook activity in a pipeline

  • Use parameters with a notebook activity