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Implement a Data Analytics Solution with Azure Databricks
Duration
1
Course
MOC-DP-3011
Available Formats
Classroom Training, Online Training
Course Description
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.This learning path helps prepare you for Exam DP-203: Data Engineering on Microsoft Azure.
Objectives
Topics
Explore Azure Databricks
- Introduction1 min
- Get started with Azure Databricks3 min
- Identify Azure Databricks workloads3 min
- Understand key concepts3 min
- Exercise - Explore Azure Databricks30 min
- Knowledge check
- Introduction
- Ingest data with Azure Databricks
- Data exploration tools in Azure Databricks
- Data analysis using DataFrame APIs
- Exercise - Explore data with Azure Databricks
- Knowledge check
- 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
- Introduction
- 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
- Knowledge check
- Introduction
- Explore Delta Live Tables
- Data ingestion and integration
- Real-time processing
- Exercise - Create a data pipeline with Delta Live Tables
- Knowledge check
- Introduction
- 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
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