04006nam a22004935i 4500 ssj0002421797 WaSeSS 20220930104639.0 m d cr n 201008s2020 xxu| o |||| 0|eng d 9781484262511 10.1007/978-1-4842-6252-8 doi WaSeSS AIMIT LIBRARY QA76.76.M52 UMP bicssc COM051380 bisacsh UMP thema 005.448 1 CHAH EBOOK Chawla, Harsh. 32728 Data lake analytics on microsoft azure practitioner's guide to big data engineering / By Harsh Chawla and Pankaj Khattar ; Foreword by Sandeep J Alur. 1st ed. Berkeley, CA : Apress : Imprint: Apress , 2020. xvii,222p. ; PB 25.5 cm text file PDF rda Chapter 1: Data Lake Analytics Concepts -- Chapter 2: Building Blocks of Data Analytics -- Chapter 3: Data Analytics on Public Cloud -- Chapter 4: Data Ingestion -- Chapter 5: Data Storage -- Chapter 6: Data Preparation and Training Part I -- Chapter 7: Data Preparation and Training Part II -- Chapter 8: Model and Serve -- Chapter 9: Summary. Requires an SPL library card. Get a 360-degree view of how the journey of data analytics solutions has evolved from monolithic data stores and enterprise data warehouses to data lakes and modern data warehouses. You will learn from the authors' experience working with large-scale enterprise customer engagements. This book includes comprehensive coverage of how: To architect data lake analytics solutions by choosing suitable technologies available on Microsoft Azure The advent of microservices applications covering ecommerce or modern solutions built on IoT and how real-time streaming data has completely disrupted this ecosystem These data analytics solutions have been transformed from solely understanding the trends from historical data to building predictions by infusing machine learning technologies into the solutions Data platform professionals who have been working on relational data stores, non-relational data stores, and big data technologies will find the content in this book useful. The book also can help you start your journey into the data engineer world as it provides an overview of advanced data analytics and touches on data science concepts and various artificial intelligence and machine learning technologies available on Microsoft Azure. You will understand the: Concepts of data lake analytics, the modern data warehouse, and advanced data analytics Architecture patterns of the modern data warehouse and advanced data analytics solutions Phases-such as Data Ingestion, Store, Prep and Train, and Model and Serve-of data analytics solutions and technology choices available on Azure under each phase In-depth coverage of real-time and batch mode data analytics solutions architecture Various managed services available on Azure such as Synapse analytics, event hubs, Stream analytics, CosmosDB, and managed Hadoop services such as Databricks and HDInsight. Mode of access: World Wide Web. Microsoft software 32729 Microsoft .NET Framework 32730 Big data 32731 Electronic books. local 32732 Khattar, Pankaj. 32733 Alur, Sandeep J. (Foreword by) 32778 Springer Nature eBook Printed edition: 9781484262511 Printed edition: 9781484262535 Printed edition: 9781484267240 View this electronic item in O'Reilly Online Learning: Academic/Public Library Edition. https://ezproxy.spl.org/login?url=https://learning.oreilly.com/library/view/~/9781484262528/?ar An e-book available through full-text database. ddc BK 1st 005.448 CHAH 222706 222706 03678120 0 0 ddc 0 0 MCA AIMIT AIMIT 2022-03-24 Biblios Book Point 849.00 Bill no:6625; Bill dt:2022-03-22 0 005.448 CHAH MCA17096 2026-05-23 00:00:00 679.20 2022-04-28 BK