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

Start met data engineering op Azure Databricks
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Cursusbeschrijving

Leer de kracht van Apache Spark en krachtige clusters op het Azure Databricks platform in te zetten om grote data engineering workloads te draaien in de cloud.

Onderwerpen

  • Module 1: Explore Azure Databricks
  • Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.
  • After completing this module, you will be able to:
  • 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
  • Azure Databricks is built on Apache Spark and enables data engineers and analysts to run Spark jobs to transform, analyze and visualize data at scale.
  • After completing this module, you will be able to:
  • 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
  • Delta Lake is an open source relational storage area for Spark that you can use to implement a data lakehouse architecture in Azure Databricks.
  • After completing this module, you will be able to:
  • 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
  • Azure Databricks provides SQL Warehouses that enable data analysts to work with data using familiar relational SQL queries.
  • After completing this module, you will be able to:
  • 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
  • Using pipelines in Azure Data Factory to run notebooks in Azure Databricks enables you to automate data engineering processes at cloud scale.
  • After completing this module, you will be able to:
  • 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.

    • Materiaal

    Digitaal Microsoft cursusmateriaal

    Voorkennis

    Kennis van data engineering en Microsoft Azure