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  • Description
  • Content
  • Target Audience
  • Certificates

In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others.

The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

LEARNING PATH 1
Get started with data engineering on Azure

  • Module 1: Introduction to data engineering on Azure
  • Module 2: Introduction to Azure Data Lake Storage Gen2
  • Module 3: Introduction to Azure Synapse Analytics

LEARNING PATH 2
Build data analytics solutions using Azure Synapse serverless SQL pools

  • Module 1: Use Azure Synapse serverless SQL pool to query files in a data lake
  • Module 2: Use Azure Synapse serverless SQL pools to transform data in a data lake
  • Module 3: Create a lake database in Azure Synapse Analytics
  • Module 4: Secure data and manage users in Azure Synapse serverless SQL pools

LEARNING PATH 3
Perform data engineering with Azure Synapse Apache Spark Pools

  • Module 1: Analyze data with Apache Spark in Azure Synapse Analytics
  • Module 2: Transform data with Spark in Azure Synapse Analytics
  • Module 3: Use Delta Lake in Azure Synapse Analytics

LEARNING PATH 4
Work with Data Warehouses using Azure Synapse Analytics

  • Module 1: Analyze data in a relational data warehouse
  • Module 2: Load data into a relational data warehouse
  • Module 3: Manage and monitor data warehouse activities in Azure Synapse Analytics
  • Module 4: Secure a data warehouse in Azure Synapse Analytics

LEARNING PATH 5
Transfer and transform data with Azure Synapse Analytics pipelines

  • Module 1: Build a data pipeline in Azure Synapse Analytics
  • Module 2: Use Spark Notebooks in an Azure Synapse Pipeline

LEARNING PATH 6
Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics

  • Module 1: Plan hybrid transactional and analytical processing using Azure Synapse Analytics
  • Module 2: Implement Azure Synapse Link with Azure Cosmos DB
  • Module 3: Implement Azure Synapse Link for SQL

LEARNING PATH 7
Implement a Data Streaming Solution with Azure Stream Analytics

  • Module 1: Get started with Azure Stream Analytics
  • Module 2: Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
  • Module 3: Visualize real-time data with Azure Stream Analytics and Power BI

LEARNING PATH 8
Govern data across an enterprise

  • Module 1: Introduction to Microsoft Purview
  • Module 2: Discover trusted data using Microsoft Purview
  • Module 3: Catalog data artifacts by using Microsoft Purview
  • Module 4: Manage Power BI assets by using Microsoft Purview
  • Module 5: Integrate Microsoft Purview and Azure Synapse Analytics

LEARNING PATH 9
Implement a Data Analytics Solution with Azure Databricks

  • Module 1: Explore Azure Databricks
  • Module 2: Use Apache Spark in Azure Databricks
  • Module 3: Use Delta Lake in Azure Databricks
  • Module 4: Use SQL Warehouses in Azure Databricks
  • Module 5: Run Azure Databricks Notebooks with Azure Data Factory

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure.

The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

Microsoft Certified: Azure Data Engineer Associate after successful completion of the Exam DP-203: Data Engineering on Microsoft Azure

Description

In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others.

The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

Content

LEARNING PATH 1
Get started with data engineering on Azure

  • Module 1: Introduction to data engineering on Azure
  • Module 2: Introduction to Azure Data Lake Storage Gen2
  • Module 3: Introduction to Azure Synapse Analytics

LEARNING PATH 2
Build data analytics solutions using Azure Synapse serverless SQL pools

  • Module 1: Use Azure Synapse serverless SQL pool to query files in a data lake
  • Module 2: Use Azure Synapse serverless SQL pools to transform data in a data lake
  • Module 3: Create a lake database in Azure Synapse Analytics
  • Module 4: Secure data and manage users in Azure Synapse serverless SQL pools

LEARNING PATH 3
Perform data engineering with Azure Synapse Apache Spark Pools

  • Module 1: Analyze data with Apache Spark in Azure Synapse Analytics
  • Module 2: Transform data with Spark in Azure Synapse Analytics
  • Module 3: Use Delta Lake in Azure Synapse Analytics

LEARNING PATH 4
Work with Data Warehouses using Azure Synapse Analytics

  • Module 1: Analyze data in a relational data warehouse
  • Module 2: Load data into a relational data warehouse
  • Module 3: Manage and monitor data warehouse activities in Azure Synapse Analytics
  • Module 4: Secure a data warehouse in Azure Synapse Analytics

LEARNING PATH 5
Transfer and transform data with Azure Synapse Analytics pipelines

  • Module 1: Build a data pipeline in Azure Synapse Analytics
  • Module 2: Use Spark Notebooks in an Azure Synapse Pipeline

LEARNING PATH 6
Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics

  • Module 1: Plan hybrid transactional and analytical processing using Azure Synapse Analytics
  • Module 2: Implement Azure Synapse Link with Azure Cosmos DB
  • Module 3: Implement Azure Synapse Link for SQL

LEARNING PATH 7
Implement a Data Streaming Solution with Azure Stream Analytics

  • Module 1: Get started with Azure Stream Analytics
  • Module 2: Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
  • Module 3: Visualize real-time data with Azure Stream Analytics and Power BI

LEARNING PATH 8
Govern data across an enterprise

  • Module 1: Introduction to Microsoft Purview
  • Module 2: Discover trusted data using Microsoft Purview
  • Module 3: Catalog data artifacts by using Microsoft Purview
  • Module 4: Manage Power BI assets by using Microsoft Purview
  • Module 5: Integrate Microsoft Purview and Azure Synapse Analytics

LEARNING PATH 9
Implement a Data Analytics Solution with Azure Databricks

  • Module 1: Explore Azure Databricks
  • Module 2: Use Apache Spark in Azure Databricks
  • Module 3: Use Delta Lake in Azure Databricks
  • Module 4: Use SQL Warehouses in Azure Databricks
  • Module 5: Run Azure Databricks Notebooks with Azure Data Factory
Target Audience

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure.

The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

Certificates

Microsoft Certified: Azure Data Engineer Associate after successful completion of the Exam DP-203: Data Engineering on Microsoft Azure

Past experiences

What people say about us

  • - Marko Krstevski Microsoft .NET Academy

    Seeking to expand my knowledge, I decided to enroll in Semos Education, where I am gaining the necessary knowledge and experience.

  • - Teodor Markovski Student

    The desire to become a Cloud architect led me to Semos Education. I am thrilled by the positive experiences of former students and the way in which the instructors and Career Center take care of the students.

  • - Viktorija Georgieva Summer Mentorship Program for Python Develope

    The reputation of Semos Education for quality training and the opportunity to learn from experienced instructors played an additional significant role in my decision.

  • - Borche Peltekovski Accredited Academy for Graphic Design

    After completing my studies at Semos Education, I envision myself working in a technology company, such as Samsung, Apple, or a company of similar caliber.

Meet the instructors

  • Dejan Vakanski  

    Microsoft Certified Trainer

    Data Consultant,

    Data Scientist @Semos Education

     

    22+ years of experience

  • Aleksandar Talev  

    Microsoft Certified Trainer

    Senior Business Intelligence Consultant 

    @HSO Global Services Macedonia

     

    25+ years of experience

  • Simka Janevska  

    Microsoft Certified Trainer

    Data and Analytics Engineer @Qinshift

     

    1+ years of experience