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Implementing a Data Analytics Solution with Azure Synapse Analytics

This is a single day Instructor Lead Course designed to give the learners instruction on the SQL dedicated and serverless Spark pools and providing instruction of data wrangling and the ELT process...

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$675 USD
Duration 1 day
Course Code DP-3012
Available Formats Classroom, Virtual

Overview

This is a single day Instructor Lead Course designed to give the learners instruction on the SQL dedicated and serverless Spark pools and providing instruction of data wrangling and the ELT process using Synapse Pipelines which is very similar to those familiar with Azure Data Factory (ADF) to move data into the Synapse dedicated pool database.

Audience Profile

The Audience should have familiarity with notebooks that use different languages and a Spark engine, such as Databricks, Jupyter Notebooks, Zeppelin notebooks and more. They should also have some experience with SQL, Python, and Azure tools, such as Data Factory.

Course Details

Outline

  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • Analyze data in a relational data warehouse
    • Design a data warehouse schema
    • Create data warehouse tables
    • Load data warehouse tables
    • Query a data warehouse
    • Exercise - Explore a data warehouse
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • Analyze data in a relational data warehouse
    • Design a data warehouse schema
    • Create data warehouse tables
    • Load data warehouse tables
    • Query a data warehouse
    • Exercise - Explore a data warehouse
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
  • 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
    • Module assessment
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Schedule

2 options available

  • Jul 17, 2025 - Jul 17, 2025 (1 day)
    Live Virtual | 9:00AM 5:00PM EDT
    Language English
    Select from 1 options below
    Live Virtual |9:00AM 5:00PM EDT
    Live Virtual | 9:00AM 5:00PM EDT
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  • Oct 24, 2025 - Oct 24, 2025 (1 day)
    Live Virtual | 9:00AM 5:00PM EDT
    Language English
    Select from 1 options below
    Live Virtual |9:00AM 5:00PM EDT
    Live Virtual | 9:00AM 5:00PM EDT
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FAQ

How do I get a Microsoft exam voucher?

Pearson Vue Exam vouchers can be requested and ordered with your course purchase or can be ordered separately by clicking here.

  • Vouchers are non-refundable and non-returnable. Vouchers expire 12 months from the date they are issued unless otherwise specified in the terms and conditions.
  • Voucher expiration dates cannot be extended. The exam must be taken by the expiration date printed on the voucher.

Do Microsoft courses come with post lab access?

Most Microsoft official courses will include post-lab access ranging from 30 to 180 calendar days after instructor led course delivery. A lab training key in class will be provided that can be leveraged to continue connecting to a remote lab environment for the individual course attendee.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour-long after 3-3.5 hours of the class day.

What languages are used to deliver training?

Microsoft courses are conducted in English unless otherwise specified.

Reviews

ExitCertified was a great. They gave me all the materials and information I needed ahead of time to prepare for the course.

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