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Implementing a Data Analytics Solution with Azure Databricks (DP-3011)

SS Course: GK834018

Course Overview

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Learn 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.

                                                                  

Scheduled Classes

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08/07/24 - GVT - Virtual Classroom - Virtual Instructor-Led
10/04/24 - GVT - Virtual Classroom - Virtual Instructor-Led
12/13/24 - GVT - Virtual Classroom - Virtual Instructor-Led
02/14/25 - GVT - Virtual Classroom - Virtual Instructor-Led

Outline

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Module 1 : Explore Azure Databricks

  • Provision an Azure Databricks workspace.
  • Identify core workloads and personas for Azure Databricks.
  • Describe key concepts of an Azure Databricks solution.

Module 2 : 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 3 : Use Delta Lake in Azure Databricks

  • Describe core features and capabilities of Delta Lake.
  • Create and use Delta Lake tables in Azure Databricks.
  • Create Spark catalog tables for Delta Lake data.
  • Use Delta Lake tables for streaming data.

Module 4 : Use SQL Warehouses in Azure Databricks

  • Create and configure SQL Warehouses in Azure Databricks.
  • Create databases and tables.
  • Create queries and dashboards.

Module 5 : 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.

    Prerequisites

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      Who Should Attend

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      Students willing to Implement a Data Analytics Solution with Azure Databricks.