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Databricks – Master Azure Databricks for Data Engineers

سرفصل های دوره

Learn Azure Databricks for professional data engineers using PySpark and Spark SQL


1. Before you start
  • 1. Course Prerequisites
  • 2. About the Course
  • 3. How to access Course Material and Resources
  • 4.1 Capstone Project.zip
  • 4.2 Notebooks.zip
  • 4.3 SampleData.zip
  • 4. Note for Students - Before Start

  • 2. Introduction
  • 1. Introduction to Data Engineering
  • 2. Apache Spark to Data Engineering Platform
  • 3.1 02-Introduction.pdf
  • 3. Introduction to Databricks Platform

  • 3. Getting Started
  • 1. What will you learn in this section
  • 2. Creating Azure Cloud Account
  • 3. Azure Portal Overview
  • 4. Creating Databricks Workspace Service
  • 5. Introduction to Databricks Workspace
  • 6.1 03-Getting Started.pdf
  • 6. Azure Databricks Platform Architecture

  • 4. Working in Databricks Workspace
  • 1. What will you learn in this section
  • 2. How to create Spark Cluster
  • 3. Working with Databricks Notebook
  • 4. Notebook Magic Commands
  • 5.1 04-Working in Databricks Workspace.pdf
  • 5.2 ch4-working in databricks workspace.zip
  • 5. Databricks Utilities Package

  • 5. Working with Databricks File System - DBFS
  • 1. What will you learn in this section
  • 2. Introduction to DBFS
  • 3. Working with DBFS Root
  • 4.1 05-Working with Databricks File System - DBFS.pdf
  • 4.2 ch5-working with databricks file system - dbfs.zip
  • 4.3 people.zip
  • 4. Mounting ADLS to DBFS

  • 6. Working with Unity Catalog
  • 1. What will you learn in this section
  • 2. Introduction to Unity Catalog
  • 3. Setup Unity Catalog
  • 4. Unity Catalog User Provisioning
  • 5.1 06-Setting up Unity Catalog.pdf
  • 5.2 ch6-working with unity catalog.zip
  • 5. Working with Securable Objects

  • 7. Working with Delta Lake and Delta Tables
  • 1. What will you learn in this section
  • 2. Introduction to Delta Lake
  • 3. Creating Delta Table
  • 4. Sharing data for External Delta Table
  • 5. Reading Delta Table
  • 6. Delta Table Operations
  • 7. Delta Table Time Travel
  • 8. Convert Parquet to Delta
  • 9. Delta Table Schema Validation
  • 10. Delta Table Schema Evolution
  • 11. Look Inside Delta Table
  • 12.1 07-Working with Delta Lake and Delta Tables.pdf
  • 12.2 CH7-Data Files.zip
  • 12.3 ch7-working with delta lake and delta tables.zip
  • 12. Delta Table Utilities and Optimization

  • 8. Working with Databricks Incremental Ingestion Tools
  • 1. What will you learn in this section
  • 2. Architecture and Need for Incremental Ingestion
  • 3. Using Copy Into with Manual Schema Evolution
  • 4. Using Copy Into with Automatic Schema Evolution
  • 5. Streaming Ingestion with Manual Schema Evolution
  • 6. Streaming Ingestion with Automatic Schema Evolution
  • 7. Introduction to Databricks Autoloader
  • 8.1 08-Working with Databricks Incremental Ingestion Tools.pdf
  • 8.2 CH8-Data Files.zip
  • 8.3 ch8-working with databricks incremental ingestion tools.zip
  • 8. Autoloader with Automatic Schema Evolution

  • 9. Working with Databricks Delta Live Tables (DLT)
  • 1. What will you learn in this section
  • 2. Introduction to Databricks DLT
  • 3. Understand DLT Use Case Scenario
  • 4. Setup DLT Scenario Dataset
  • 5. Creating DLT Workload in SQL
  • 6. Creating DLT Pipeline for your Workload
  • 7.1 09-Working with Databricks Delta Live Tables (DLT).pdf
  • 7.2 CH9-Data Files.zip
  • 7.3 ch9-working with databricks delta live tables (dlt).zip
  • 7. Creating DLT Workload in Python

  • 10. Databricks Project and Automation Features
  • 1. What will you learn in this section
  • 2. Working with Databricks Repos
  • 3. Working with Databricks Workflows
  • 4. Working with Databricks Rest API
  • 5.1 10-Databricks Project and Automation Features.pdf
  • 5.2 CH10-Data Files.zip
  • 5.3 ch10-databricks project and automation features.zip
  • 5.4 Deploy.zip
  • 5. Working with Databricks CLI

  • 11. Capstone Project
  • 1. Project Scope and Background
  • 2. Taking out the operational requirement
  • 3. Storage Design
  • 4. Implement Data Security
  • 5. Implement Resource Policies
  • 6. Decouple Data Ingestion
  • 7. Design Bronze Layer
  • 8. Design Silver and Gold Layer
  • 9. Setup your environment
  • 10. Create a workspace
  • 11. Create and Storage Layer
  • 12. Setup Unity Catalog
  • 13. Create Metadata Catalog and External Locations
  • 14. Setup your source control
  • 15. Start Coding
  • 16. Test your code
  • 17. Load historical data
  • 18. Ingest into bronze layer
  • 19. Process the silver layer
  • 20. Handling multiple updates
  • 21. Implementing Gold Layer
  • 22. Creating a run script
  • 23. Preparing for Integration testing
  • 24. Creating Test Data Producer
  • 25. Creating Integration Test for Batch mode
  • 26. Creating Integration Test for Stream mode
  • 27. Implementing CI CD Pipeline
  • 28. Develop Build Pipeline
  • 29. Develop Release Pipeline
  • 30.1 Data Set.zip
  • 30.2 Notebooks.zip
  • 30.3 Other Code.zip
  • 30. Creating Databricks CLI Script

  • 12. Final Word
  • 1. Congratulations
  • 2. Keep Learning and Keep Growing.html
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