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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.

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What You'll Learn

  • Provision an Azure Databricks workspace.
  • Identify core workloads and personas for Azure Databricks.
  • Describe key concepts of an Azure Databricks solution.
  • 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.
  • 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.
  • Create and configure SQL Warehouses in Azure Databricks.
  • Create databases and tables.
  • Create queries and dashboards.
  • 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.

Who Should Attend

N/A

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Prerequisites

Please review the prerequisites listed for each module in the course content and click on the provided links for more information.

Learning Journey

Coming Soon...

1. Explore Azure Databricks

Azure Databricks is a cloud service that provides a scalable platform for data analytics using Apache Spark.

Click here to know more

2. Perform data analysis with Azure Databricks

Learn how to perform data analysis using Azure Databricks. Explore various data ingestion methods and how to integrate data from sources like Azure Data Lake and Azure SQL Database. This module guides you through using collaborative notebooks to perform exploratory data analysis (EDA), so you can visualize, manipulate, and examine data to uncover patterns, anomalies, and correlations.

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3. 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.

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4. Manage data with Delta Lake

Delta Lake is a data management solution in Azure Databricks providing features including ACID transactions, schema enforcement, and time travel ensuring data consistency, integrity, and versioning capabilities.

Click here to know more

5. Build data pipelines with Delta Live Tables

Building data pipelines with Delta Live Tables enables real-time, scalable, and reliable data processing using Delta Lake's advanced features in Azure Databricks

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6. Deploy workloads with Azure Databricks Workflows

Deploying workloads with Azure Databricks Workflows involves orchestrating and automating complex data processing pipelines, machine learning workflows, and analytics tasks. In this module, you learn how to deploy workloads with Databricks Workflows.

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Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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