Simplify data analytics in Azure for building end-to-end big data solutions, leveraging AI, and working with large datasets in a highly available cloud environment Key Features Boost Azure Databricks by building and optimizing compute clusters for effective solutions Elevate data solutions by leveraging OpenAI and Microsoft Fabric integration in Azure Databricks Secure Azure Operations with high availability, disaster recovery, and Unity Catalog governance Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe second edition of Azure Databricks Cookbook offers hands-on recipes for ingesting and governing data, building modern data warehouses, and creating innovative AI solutions using Azure Databricks. Starting with creating an Azure Databricks instance, you'll explore clusters and ingest data from various sources like files, databases, and streaming platforms such as Apache Kafka and EventHub. You'll learn how to load data in the Azure Databricks Lakehouse and cover end-to-end data pipelines, utilizing Delta tables and Azure Synapse Analytics for building a modern data warehouse. As you progress, you’ll also learn how to visualize insights and create dashboards with Databricks SQL and deploy and productionalize data pipelines using CI/CD for Azure Databricks notebooks. This book will also guide you through setting up Unity Catalog as well as configuring metastore, catalogs, databases, and tables. You’ll get to grips with ensuring operations continuity with high availability and disaster recovery planning. Finally, you'll explore how to modernize workloads with artificial intelligence and cost-efficient administration. By the end of this book, you’ll have unlocked transformational insights from data, mastered predictive modeling techniques, and understood development operations best practices to optimize your data solutions.What you will learn Build a modern data warehouse with Delta tables and Azure Synapse Analytics Create real-time dashboards in Databricks SQL Implement data governance with Unity Catalog Build end-to-end data processing pipelines for near real-time data analytics Integrate Azure DevOps for version control as well as for deploying and productionizing solutions with continuous integration and continuous deployment (CI/CD) pipelines Enhance Azure Databricks with OpenAI and Microsoft Fabric integration for cutting-edge data solutions Who this book is forThis recipe-based Databricks book is for data engineers, data scientists, big data professionals, and machine learning engineers who want to perform data analytics on massive datasets. Prior experience with Apache Spark and Microsoft Azure is necessary to get the most out of this book.
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Table of Contents
  1. Creating an Azure Databricks Workspace
  2. Reading and Writing Data from and to Various Azure Services and File Formats
  3. Reading and Loading Data in the Azure Databricks Lakehouse
  4. Understanding Spark Query Execution
  5. Exploring Delta Lake in Azure Databricks
  6. Working with Streaming Data
  7. Integration with Azure Key-Vault, App Configuration and Log Analytics
  8. Implementing Near-Real-Time Analytics and Building a Modern Data Warehouse
  9. Azure Databricks SQL Analytics
  10. DevOps Integrations and Implementing CI/CD for Azure Databricks
  11. Governing Your Data Estate with Unity Catalog- Setup
  12. Governing Your Data Estate with Unity Catalog- Exploration and Management
  13. Understanding Security and Monitoring in Azure Databricks
  14. Ensuring Operations Continuity with High Availability and Disaster Recovery Planning
  15. Microsoft Fabric & Databricks
  16. Prompt Engineering
  17. Advanced AI Features in Databricks
  18. Azure Databricks Best Practices and Optimization
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Produktdetaljer

ISBN
9781805123828
Utgave
2. utgave
Utgiver
Packt Publishing Limited
Høyde
235 mm
Bredde
191 mm
Aldersnivå
01, G, 01
Språk
Product language
Engelsk
Format
Product format
Heftet
Antall sider
767

Biografisk notat

M. Lynne Alanfield is an experienced and dynamic Principal Cloud Solution Architect. She works with Microsoft's most strategic global customers to discover, migrate and plan business transformation through Microsoft's Azure cloud. She is an award winning subject matter expert in Azure Data Cloud and Artificial Intelligence and a recognized Global Business Intelligence Lead within Microsoft. Melissa is renowned for delivering cutting-edge services for large, global enterprise customers. With a PhD in Cybersecurity and masters and bachelors in MIS, she has an impressive academic background that she supplements through her strong technical writing skills and best-selling author status in non-technical genres. Jeremy Peach is a data scientist with twenty years of experience turning data into insights. As a Senior Cloud Solution Architect at Microsoft, he specializes in Azure Databricks and helps large enterprises around the world solve their toughest analytical challenges using Azure and Apache Spark. He has written several articles on harnessing the power of the cloud to create data science solutions and scaling up analysis of big data.