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Asseco Academy » Training » Implementing a Data Analytics Solution with Azure Databricks

Training DP-3011

Implementing a Data Analytics Solution with Azure Databricks

Accreditation

  • Training description
  • Scope

Training description

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. model.migration.

Prerequisites

  • None

Scope

  • Explore Azure Databricks
    • Introduction
    • Get started with Azure Databricks
    • Identify Azure Databricks workloads
    • Understand key concepts
    • Data governance using Unity Catalog and Microsoft Purview
    • Exercise – Explore Azure Databricks
  • Perform data analysis with Azure Databricks
    • Ingest data with Azure Databricks
    • Data exploration tools in Azure Databricks
    • Data analysis using DataFrame APIs
    • Exercise – Explore data with Azure Databricks
  • Use Apache Spark in Azure Databricks
    • 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
  • Manage data with Delta Lake
    • Get started with Delta Lake
    • Manage ACID transactions
    • Implement schema enforcement
    • Data versioning and time travel in Delta Lake
    • Data integrity with Delta Lake
    • Exercise – Use Delta Lake in Azure Databricks
  • Build data pipelines with Delta Live Tables
    • Explore Delta Live Tables
    • Data ingestion and integration
    • Real-time processing
    • Exercise – Create a data pipeline with Delta Live Tables
  • Deploy workloads with Azure Databricks Workflows
    • What are Azure Databricks Workflows?
    • Understand key components of Azure Databricks Workflows
    • Explore the benefits of Azure Databricks Workflows
    • Deploy workloads using Azure Databricks Workflows
    • Exercise – Create an Azure Databricks Workflow
    • Knowledge check
    • Summary

Training schedule

Remote

… if you value the opportunity to learn with a trainer and other participants, from anywhere without having to commute.

Stationary

… if you want to learn while sitting in the same room with the trainer and other participants.

Online

… if you want to learn from materials available via the interenet anywhere at any time

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Implementing a Data Analytics Solution with Azure Databricks

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