LEADER 00889nam 2200253la 450 001 9910481769403321 005 20221108091447.0 035 $a(UK-CbPIL)2090308799 035 $a(CKB)5500000000086177 035 $a(EXLCZ)995500000000086177 100 $a20210618f16001650 uy | 101 0 $adut 135 $aurcn||||a|bb| 200 10$aHaerlems oudt liedt-boeck, inhoudende veele historiale ende amoureuse liedekens$b[electronic resource] 210 $aHaarlem $cVincent >Casteleyn$d[1600-1650?] 215 $aOnline resource (8° obl) 300 $aReproduction of original in Koninklijke Bibliotheek, Nationale bibliotheek van Nederland. 700 $aAnon$0815482 801 0$bUk-CbPIL 801 1$bUk-CbPIL 906 $aBOOK 912 $a9910481769403321 996 $aHaerlems oudt liedt-boeck, inhoudende veele historiale ende amoureuse liedekens$92059421 997 $aUNINA LEADER 03524nam 22004453 450 001 9911046616603321 005 20241006090236.0 010 $a9788196862046 010 $a8196862040 035 $a(MiAaPQ)EBC31707320 035 $a(Au-PeEL)EBL31707320 035 $a(CKB)36271195800041 035 $a(Exl-AI)31707320 035 $a(OCoLC)1492932263 035 $a(EXLCZ)9936271195800041 100 $a20241006d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMastering Data Engineering and Analytics with Databricks $eA Hands-On Guide to Build Scalable Pipelines Using Databricks, Delta Lake, and MLflow (English Edition) 205 $a1st ed. 210 1$aDelhi :$cOrange Education PVT Ltd,$d2024. 210 4$dİ2024. 215 $a1 online resource (331 pages) 327 $aCover Page -- Title Page -- Copyright Page -- Dedication Page -- About the Author -- About the Technical Reviewers -- Acknowledgements -- Preface -- Errata -- Table of Contents -- SECTION 1 Getting Started with Data Engineering and Databricks -- 1. Introducing Data Engineering with Databricks -- Introduction -- Structure -- The Basics of Data Engineering -- Data -- Data Layers -- Raw Data -- Enriched Data -- Curated Data -- Big Data -- Data Quality -- Master Data/Dimensions -- Transactions/Facts -- Times Series Data -- Data Serialization -- Parquet -- JavaScript Object Notation (JSON) -- Comma Separated Values (CSV) -- Schema$7Generated by AI. 330 $aIn today's data-driven world, mastering data engineering is crucial for driving innovation and delivering real business impact. Databricks is one of the most powerful platforms which unifies data, analytics and AI requirements of numerous organizations worldwide. Mastering Data Engineering and Analytics with Databricks goes beyond the basics, offering a hands-on, practical approach tailored for professionals eager to excel in the evolving landscape of data engineering and analytics. This book uniquely blends foundational knowledge with advanced applications, equipping readers with the expertise to build, optimize, and scale data pipelines that meet real-world business needs. With a focus on actionable learning, it delves into complex workflows, including real-time data processing, advanced optimization with Delta Lake, and seamless ML integration with MLflow--skills critical for today's data professionals. Drawing from real-world case studies in FMCG and CPG industries, this book not only teaches you how to implement Databricks solutions but also provides strategic insights into tackling industry-specific challenges. From setting up your environment to deploying CI/CD pipelines, you'll gain a competitive edge by mastering techniques that are directly applicable to your organization's data strategy. By the end, you'll not just understand Databricks--you'll command it, positioning yourself as a leader in the data engineering space. 606 $aBig data$7Generated by AI 606 $aData mining$7Generated by AI 615 0$aBig data 615 0$aData mining 700 $aKumar$b Manoj$0720895 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911046616603321 996 $aMastering Data Engineering and Analytics with Databricks$94468369 997 $aUNINA