Home

Books

Computers & Technology

Packt Azure Databricks Cookbook: Accelerate and scale real-time analytics solutions using the Apache Spark-based analytics service

228.00

Inclusive of VAT

Free Delivery

Get it by 21 - 24 June

Order in 19 h 3 m

Delivery by noon

High Rated Seller

Cash on Delivery

Secure Transaction

BANK OFFERS

Earn 5% cashback with the Mashreq noon Credit Card.

SELLER

Item as shown

Partner since

Free delivery on Lockers & Pickup Points

This item is eligible for free returns

Product Overview

Specifications

Publisher	Packt Publishing
ISBN 13	9781789809718
ISBN 10	1789809711
Author	Phani Raj
Book Format	Paperback

Language	English
Book Description	Get to grips with building and productionizing end-to-end big data solutions in Azure and learn best practices for working with large datasetsKey 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 environmentsBook 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: Read and write data from and to various Azure resources and file formatsBuild a modern data warehouse with Delta Tables and Azure Synapse AnalyticsExplore jobs, stages, and tasks and see how Spark lazy evaluation worksHandle concurrent transactions and learn performance optimization in Delta tablesLearn Databricks SQL and create real-time dashboards in Databricks SQLIntegrate Azure DevOps for version control, deploying, and productionizing solutions with CI/CD pipelinesDiscover how to use RBAC and ACLs to restrict data accessBuild end-to-end data processing pipeline for near real-time data analyticsWho 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.
About the Author	Phani Raj is an Azure data architect at Microsoft. He has more than 12 years of IT experience and works primarily on the architecture, design, and development of complex data warehouses, OLTP, and big data solutions on Azure for customers across the globe.Vinod Jaiswal is a data engineer at Microsoft. He has more than 13 years of IT experience and works primarily on the architecture, design, and development of complex data warehouses, OLTP, and big data solutions on Azure using Azure data services for a variety of customers. He has also worked on designing and developing real-time data processing and analytics reports from the data ingested from streaming systems using Azure Databricks.
Publication Date	17 September 2021
Number of Pages	452 pages

Cart Total  228.00