Get to grips with building and productionizing end-to-end big data solutions in Azure and learn best practices for working with large datasets
Key Features:Integrate with Azure Synapse Analytics, Cosmos DB, and Azure HDInsight Kafka Cluster to scale and analyze your projects and build pipelinesUse Databricks SQL to run ad hoc queries on your data lake and create dashboardsProductionize a solution using CI/CD for deploying notebooks and Azure Databricks Service to various environments
Book Description:Azure Databricks is a unified collaborative platform for performing scalable analytics in an interactive environment. The Azure Databricks Cookbook provides recipes to get hands-on with the analytics process, including ingesting data from various batch and streaming sources and building a modern data warehouse.
The book starts by teaching you how to create an Azure Databricks instance within the Azure portal, Azure CLI, and ARM templates. You'll work through clusters in Databricks and explore recipes for ingesting data from sources, including files, databases, and streaming sources such as Apache Kafka and EventHub. The book will help you explore all the features supported by Azure Databricks for building powerful end-to-end data pipelines. You'll also find out how to build a modern data warehouse by using Delta tables and Azure Synapse Analytics. Later, you'll learn how to write ad hoc queries and extract meaningful insights from the data lake by creating visualizations and dashboards with Databricks SQL. Finally, you'll deploy and productionize a data pipeline as well as deploy notebooks and Azure Databricks service using continuous integration and continuous delivery (CI/CD).
By the end of this Azure book, you'll be able to use Azure Databricks to streamline different processes involved in building data-driven apps.
What You Will Learn:Understand Databricks cluster options and when to use themRead and write data from and to Azure sources such as ADLS Gen-2, EventHub, and moreBuild a data warehouse in Azure DatabricksPerform ad hoc analysis on data lakes using Databricks SQL AnalyticsIntegrate with Azure Key Vault to access hidden data and Log Analytics for telemetry and monitoringIntegrate Databricks with Azure DevOps for version control and for deployment and to productionize the solution using CI/CD pipelinesBuild a data processing pipeline for near real-time data analytics
Who this book is for:This recipe-based book is for data scientists, data engineers, big data professionals, and machine learning engineers who want to perform data analytics on their applications. Prior experience of working with Apache Spark and Azure is necessary to get the most out of this book.

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