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Implementing a Data Analytics Solution with Azure Databricks

  • CMDBID 1170
  • Course Code MDP3011
  • Duration 1 Days
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Microsoft Azure Course

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Overview

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.

Outline

Module 1: Explore Azure Databricks
Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.
  • Introduction
  • Get started with Azure Databricks
  • Identify Azure Databricks workloads
  • Understand key concepts
  • Exercise - Explore Azure Databricks
  • Knowledge check
  • Summary
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.
  • Introduction
  • Get to know Spark
  • Create a Spark cluster
  • Use Spark in notebooks
  • Use Spark to work with data files
  • Visualize data
  • Exercise - Use Spark in Azure Databricks
  • Knowledge check
  • Summary
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.
  • Introduction
  • Get Started with Delta Lake
  • Create Delta Lake tables
  • Create and query catalog tables
  • Use Delta Lake for streaming data
  • Exercise - Use Delta Lake in Azure Databricks
  • Knowledge check
  • Summary
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.
  • Introduction
  • Get started with SQL Warehouses
  • Create databases and tables
  • Create queries and dashboards
  • Exercise - Use a SQL Warehouse in Azure Databricks
  • Knowledge check
  • Summary
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.
  • Introduction
  • Understand Azure Databricks notebooks and pipelines
  • Create a linked service for Azure Databricks
  • Use a Notebook activity in a pipeline
  • Use parameters in a notebook
  • Exercise - Run an Azure Databricks Notebook with Azure Data Factory
  • Knowledge check
  • Summary

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