Implementing a Data Analytics Solution with Azure Databricks
- Course Code M-DP3011
- Duration 1 day
Course Delivery
Course Delivery
This course is available in the following formats:
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Company Event
Event at company
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Public Classroom
Traditional Classroom Learning
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Virtual Learning
Learning that is virtual
Request this course in a different delivery format.
Course Overview
TopLearn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run large data engineering workloads in the cloud.
Course Schedule
Top-
- Delivery Format: Public Classroom
- Date: 21 September, 2026 | 9:00 AM to 5:00 PM
- Location: Groningen/Paterswolde (Groningerweg 19) (W. Europe Standard Time)
- Language: Dutch
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- Delivery Format: Virtual Learning
- Date: 21 September, 2026 | 9:00 AM to 5:00 PM
- Location: Virtual (W. Europe Standard Time)
- Language: Dutch
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- Delivery Format: Virtual Learning
- Date: 06 October, 2026 | 9:30 AM to 5:30 PM
- Location: Virtual (W. Europe Standard Time)
- Language: French
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- Delivery Format: Virtual Learning
- Date: 02 November, 2026 | 9:00 AM to 5:00 PM
- Location: Virtual (W. Europe Standard Time)
- Language: Spanish
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- Delivery Format: Virtual Learning
- Date: 16 November, 2026 | 8:00 AM to 4:00 PM
- Location: Virtual (GMT Standard Time)
- Language: English
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- Delivery Format: Public Classroom
- Date: 16 November, 2026 | 9:00 AM to 5:00 PM
- Location: 1-Mechelen (Battelsesteenweg 455-B) (W. Europe Standard Time)
- Language: English
Course Objectives
Top- Explore Azure Databricks
- Perform data analysis with Azure Databricks
- Use Apache Spark in Azure Databricks
- Manage data with Delta Lake
- Build data pipelines with Delta Live Tables
- Deploy workloads with Azure Databricks Workflows
- Use SQL Warehouses in Azure Databricks
- Run Azure Databricks Notebooks with Azure Data Factory
Course Content
TopModule 1 : Explore Azure Databricks
- Provision an Azure Databricks workspace
- Identify core workloads for Azure Databricks
- Use Data Governance tools Unity Catalog and Microsoft Purview
- Describe key concepts of an Azure Databricks solution
Module 2 : Perform data analysis with Azure Databricks
- Ingest data using Azure Databricks.
- Using the different data exploration tools in Azure Databricks.
- Analyze data with DataFrame APIs.
Module 3 : Use Apache Spark in Azure Databricks
- Describe key elements of the Apache Spark architecture.
- Create and configure a Spark cluster.
- Describe use cases for Spark.
- Use Spark to process and analyze data stored in files.
- Use Spark to visualize data.
Module 4 : Manage data with Delta Lake
- What Delta Lake is
- How to manage ACID transactions using Delta Lake
- How to use schema versioning and time travel in Delta Lake
- How to maintain data integrity with Delta Lake
Module 5 : Build data pipelines with Delta Live Tables
- Describe Delta Live Tables
- Ingest data into Delta Live Tables
- Use Data Pipelines for real time data processing
Module 6 : Deploy workloads with Azure Databricks Workflows
- What Azure Databricks Workflows are
- The key components and benefits of Azure Databricks Workflows
- How to deploy workloads using Azure Databricks Workflows
Module 7 : Use SQL Warehouses in Azure Databricks
- Create and configure SQL Warehouses in Azure Databricks.
- Create databases and tables.
- Create queries and dashboards.
Module 8 : Run Azure Databricks Notebooks with Azure Data Factory
- Describe how Azure Databricks notebooks can be run in a pipeline.
- Create an Azure Data Factory linked service for Azure Databricks.
- Use a Notebook activity in a pipeline.
- Pass parameters to a notebook.
Course Prerequisites
TopNone
