LEADER 03793nam 2200529 450 001 9910427051203321 005 20210303233922.0 010 $a1-4842-6252-2 024 7 $a10.1007/978-1-4842-6252-8 035 $a(CKB)4100000011493404 035 $a(DE-He213)978-1-4842-6252-8 035 $a(MiAaPQ)EBC6370241 035 $a(CaSebORM)9781484262528 035 $a(PPN)252511662 035 $a(EXLCZ)994100000011493404 100 $a20210303d2020 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aData lake analytics on Microsoft Azure $ea practitioner's guide to big data engineering /$fHarsh Chawla; Pankaj Khattar; Sandeep J. Alur 205 $a1st ed. 2020. 210 1$aNew York, New York :$cApress L. P.,$d[2020] 210 4$dİ2020 215 $a1 online resource (XVII, 222 p. 134 illus.) 300 $aIncludes index. 311 $a1-4842-6251-4 327 $aChapter 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. 330 $aGet 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. 606 $aBig data 606 $aMicrosoft Azure (Computing platform) 606 $aMicrosoft .NET Framework 615 0$aBig data. 615 0$aMicrosoft Azure (Computing platform) 615 0$aMicrosoft .NET Framework. 676 $a004.165 700 $aChawla$b Harsh$0995906 702 $aKhattar$b Pankaj 702 $aAlur$b J. Sandeep 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910427051203321 996 $aData lake analytics on Microsoft Azure$92282142 997 $aUNINA