Using R To Unlock The Value Of Big Data Big Data Analytics With Oracle R Enterprise And Oracle R Connector For Hadoop

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Using R to Unlock the Value of Big Data: Big Data Analytics with Oracle R Enterprise and Oracle R Connector for Hadoop

Author : Mark Hornick
Publisher : McGraw Hill Professional
ISBN 13 : 0071826270
Total Pages : 83 pages
Book Rating : 4.0/5 (718 download)

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Book Synopsis Using R to Unlock the Value of Big Data: Big Data Analytics with Oracle R Enterprise and Oracle R Connector for Hadoop by : Mark Hornick

Download or read book Using R to Unlock the Value of Big Data: Big Data Analytics with Oracle R Enterprise and Oracle R Connector for Hadoop written by Mark Hornick and published by McGraw Hill Professional. This book was released on 2013-06-14 with total page 83 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Oracle Press Guide to Big Data Analytics using R Cowritten by members of the Big Data team at Oracle, this Oracle Press book focuses on analyzing data with R while making it scalable using Oracle’s R technologies. Using R to Unlock the Value of Big Data provides an introduction to open source R and describes issues with traditional R and database interaction. The book then offers in-depth coverage of Oracle’s strategic R offerings: Oracle R Enterprise, Oracle R Distribution, ROracle, and Oracle R Connector for Hadoop. You can practice your new skills using the end-of-chapter exercises.

Fundamentals of Big Data Analytics

Author : Dr.T.Vijaya Saradhi
Publisher : GCS PUBLISHERS
ISBN 13 : 939430438X
Total Pages : 263 pages
Book Rating : 4.3/5 (943 download)

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Book Synopsis Fundamentals of Big Data Analytics by : Dr.T.Vijaya Saradhi

Download or read book Fundamentals of Big Data Analytics written by Dr.T.Vijaya Saradhi and published by GCS PUBLISHERS. This book was released on 2022-05-02 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundamentals of Big Data Analytics written by Dr.Thomman Vijaya SaradhiDr. Syed Azahad Mr .Sreejith R, Dr. Sreekumar Narayanan

Modern Approaches for Intelligent Information and Database Systems

Author : Andrzej Sieminski
Publisher : Springer
ISBN 13 : 3319760815
Total Pages : 521 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Modern Approaches for Intelligent Information and Database Systems by : Andrzej Sieminski

Download or read book Modern Approaches for Intelligent Information and Database Systems written by Andrzej Sieminski and published by Springer. This book was released on 2018-02-23 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a unique blend of reports on both theoretical models and their applications in the area of Intelligent Information and Database Systems. The reports cover a broad range of research topics, including advanced learning techniques, knowledge engineering, Natural Language Processing (NLP), decision support systems, Internet of things (IoT), computer vision, and tools and techniques for Intelligent Information Systems. They are extended versions of papers presented at the ACIIDS 2018 conference (10th Asian Conference on Intelligent Information and Database Systems), which was held in Dong Hoi City, Vietnam on 19–21 March 2018. What all researchers and students of computer science need is a state-of-the-art report on the latest trends in their respective areas of interest. Over the years, researchers have proposed increasingly complex theoretical models, which provide the theoretical basis for numerous applications. The applications, in turn, have a profound influence on virtually every aspect of human activities, while also allowing us to validate the underlying theoretical concepts.

Oracle R Enterprise: Harnessing the Power of R in Oracle Database

Author : Brendan Tierney
Publisher : McGraw Hill Professional
ISBN 13 : 1259585646
Total Pages : 253 pages
Book Rating : 4.2/5 (595 download)

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Book Synopsis Oracle R Enterprise: Harnessing the Power of R in Oracle Database by : Brendan Tierney

Download or read book Oracle R Enterprise: Harnessing the Power of R in Oracle Database written by Brendan Tierney and published by McGraw Hill Professional. This book was released on 2016-11-04 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the Big Data Capabilities of Oracle R Enterprise Effectively manage your enterprise’s big data and keep complex processes running smoothly using the hands-on information contained in this Oracle Press guide. Oracle R Enterprise: Harnessing the Power of R in Oracle Database shows, step-by-step, how to create and execute large-scale predictive analytics and maintain superior performance. Discover how to explore and prepare your data, accurately model business processes, generate sophisticated graphics, and write and deploy powerful scripts. You will also find out how to effectively incorporate Oracle R Enterprise features in APEX applications, OBIEE dashboards, and Apache Hadoop systems. Learn to: • Install, configure, and administer Oracle R Enterprise • Establish connections and move data to the database • Create Oracle R Enterprise packages and functions • Use the R language to work with data in Oracle Database • Build models using ODM, ORE, and other algorithms • Develop and deploy R scripts and use the R script repository • Execute embedded R scripts and employ ORE SQL API functions • Map and manipulate data using Oracle R Advanced Analytics for Hadoop • Use ORE in Oracle Data Miner, OBIEE, and other applications

Oracle Big Data Handbook

Author : Tom Plunkett
Publisher : McGraw Hill Professional
ISBN 13 : 0071827269
Total Pages : 467 pages
Book Rating : 4.0/5 (718 download)

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Book Synopsis Oracle Big Data Handbook by : Tom Plunkett

Download or read book Oracle Big Data Handbook written by Tom Plunkett and published by McGraw Hill Professional. This book was released on 2013-09-25 with total page 467 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Cowritten by members of Oracle's big data team, [this book] provides complete coverage of Oracle's comprehensive, integrated set of products for acquiring, organizing, analyzing, and leveraging unstructured data. The book discusses the strategies and technologies essential for a successful big data implementation, including Apache Hadoop, Oracle Big Data Appliance, Oracle Big Data Connectors, Oracle NoSQL Database, Oracle Endeca, Oracle Advanced Analytics, and Oracle's open source R offerings"--Page 4 of cover.

Data Science Using Oracle Data Miner and Oracle R Enterprise

Author : Sibanjan Das
Publisher : Apress
ISBN 13 : 1484226143
Total Pages : 300 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Data Science Using Oracle Data Miner and Oracle R Enterprise by : Sibanjan Das

Download or read book Data Science Using Oracle Data Miner and Oracle R Enterprise written by Sibanjan Das and published by Apress. This book was released on 2016-12-22 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes. Data Science Automation Using Oracle Data Miner and Oracle R Enterprise starts with an introduction to business analytics, covering why automation is necessary and the level of complexity in automation at each analytic stage. Then, it focuses on how predictive analytics can be automated by using Oracle Data Miner and Oracle R Enterprise. Also, it explains when and why ODM and ORE are to be used together for automation. The subsequent chapters detail various statistical processes used for predictive analytics such as calculating attribute importance, clustering methods, regression analysis, classification techniques, ensemble models, and neural networks. In these chapters you will also get to understand the automation processes for each of these statistical processes using ODM and ORE along with their application in a real-life business use case. What you'll learn Discover the functionality of Oracle Data Miner and Oracle R Enterprise Gain methods to perform in-database predictive analytics Use Oracle's SQL and PLSQL APIs for building analytical solutions Acquire knowledge of common and widely-used business statistical analysis techniques Who this book is for IT executives, BI architects, Oracle architects and developers, R users and statisticians.

Trino: The Definitive Guide

Author : Matt Fuller
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098107683
Total Pages : 310 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Trino: The Definitive Guide by : Matt Fuller

Download or read book Trino: The Definitive Guide written by Matt Fuller and published by "O'Reilly Media, Inc.". This book was released on 2021-04-14 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine. With this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production engineers will learn how to manage, use, and even develop with Trino. Initially developed by Facebook, open source Trino is now used by Netflix, Airbnb, LinkedIn, Twitter, Uber, and many other companies. Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Trino query can combine data from multiple sources to allow for analytics across your entire organization. Get started: Explore Trino's use cases and learn about tools that will help you connect to Trino and query data Go deeper: Learn Trino's internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and more Put Trino in production: Secure Trino, monitor workloads, tune queries, and connect more applications; learn how other organizations apply Trino

Big Data Analytics with R and Hadoop

Author : Vignesh Prajapati
Publisher :
ISBN 13 : 9781782163282
Total Pages : 0 pages
Book Rating : 4.1/5 (632 download)

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Book Synopsis Big Data Analytics with R and Hadoop by : Vignesh Prajapati

Download or read book Big Data Analytics with R and Hadoop written by Vignesh Prajapati and published by . This book was released on 2013 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.

Big Data Analytics with R

Author : Simon Walkowiak
Publisher : Packt Publishing Ltd
ISBN 13 : 1786463725
Total Pages : 498 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Big Data Analytics with R by : Simon Walkowiak

Download or read book Big Data Analytics with R written by Simon Walkowiak and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets.

Data Science and Big Data Analytics

Author : EMC Education Services
Publisher : John Wiley & Sons
ISBN 13 : 1118876059
Total Pages : 432 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Data Science and Big Data Analytics by : EMC Education Services

Download or read book Data Science and Big Data Analytics written by EMC Education Services and published by John Wiley & Sons. This book was released on 2015-01-05 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data Learn how to tell a compelling story with data to drive business action Prepare for EMC Proven Professional Data Science Certification Get started discovering, analyzing, visualizing, and presenting data in a meaningful way today!

Handbook of Research on Cloud Infrastructures for Big Data Analytics

Author : Raj, Pethuru
Publisher : IGI Global
ISBN 13 : 1466658657
Total Pages : 592 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Handbook of Research on Cloud Infrastructures for Big Data Analytics by : Raj, Pethuru

Download or read book Handbook of Research on Cloud Infrastructures for Big Data Analytics written by Raj, Pethuru and published by IGI Global. This book was released on 2014-03-31 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clouds are being positioned as the next-generation consolidated, centralized, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional applications and services. Handbook of Research on Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organizations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.

Big Data Analytics with R

Author : Simon Walkowiak
Publisher : Packt Publishing
ISBN 13 : 9781786466457
Total Pages : 506 pages
Book Rating : 4.4/5 (664 download)

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Book Synopsis Big Data Analytics with R by : Simon Walkowiak

Download or read book Big Data Analytics with R written by Simon Walkowiak and published by Packt Publishing. This book was released on 2016-07-29 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt:

R Programming: An Approach to Data Analytics

Author : G. Sudhamathy, C. Jothi Venkateswaran
Publisher : MJP Publisher
ISBN 13 :
Total Pages : 383 pages
Book Rating : 4./5 ( download)

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Book Synopsis R Programming: An Approach to Data Analytics by : G. Sudhamathy, C. Jothi Venkateswaran

Download or read book R Programming: An Approach to Data Analytics written by G. Sudhamathy, C. Jothi Venkateswaran and published by MJP Publisher. This book was released on 2019-06-03 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapter 1 - Basics of R, Chapter 2 - Data Types in R , Chapter 3 - Data Preparation. Chapter 4 - Graphics using R, Chapter 5 - Statistical Analysis Using R, Chapter 6 - Data Mining Using R, Chapter 7 - Case Studies. Huge volumes of data are being generated by many sources like commercial enterprises, scientific domains and general public daily. According to a recent research, data production will be 44 times greater in 2020 than it was in 2010. Data being a vital resource for business organizations and other domains like education, health, manufacturing etc., its management and analysis is becoming increasingly important. This data, due to its volume, variety and velocity, often referred to as Big Data, also includes highly unstructured data in the form of textual documents, web pages, graphical information and social media comments. Since Big Data is characterised by massive sample sizes, high dimensionality and intrinsic heterogeneity, traditional approaches to data management, visualisation and analytics are no longer satisfactorily applicable. There is therefore an urgent need for newer tools, better frameworks and workable methodologies for such data to be appropriately categorised, logically segmented, efficiently analysed and securely managed. This requirement has resulted in an emerging new discipline of Data Science that is now gaining much attention with researchers and practitioners in the field of Data Analytics.

Building Big Data and Analytics Solutions in the Cloud

Author : Wei-Dong Zhu
Publisher : IBM Redbooks
ISBN 13 : 0738453994
Total Pages : 101 pages
Book Rating : 4.7/5 (384 download)

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Book Synopsis Building Big Data and Analytics Solutions in the Cloud by : Wei-Dong Zhu

Download or read book Building Big Data and Analytics Solutions in the Cloud written by Wei-Dong Zhu and published by IBM Redbooks. This book was released on 2014-12-08 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data is currently one of the most critical emerging technologies. Organizations around the world are looking to exploit the explosive growth of data to unlock previously hidden insights in the hope of creating new revenue streams, gaining operational efficiencies, and obtaining greater understanding of customer needs. It is important to think of big data and analytics together. Big data is the term used to describe the recent explosion of different types of data from disparate sources. Analytics is about examining data to derive interesting and relevant trends and patterns, which can be used to inform decisions, optimize processes, and even drive new business models. With today's deluge of data comes the problems of processing that data, obtaining the correct skills to manage and analyze that data, and establishing rules to govern the data's use and distribution. The big data technology stack is ever growing and sometimes confusing, even more so when we add the complexities of setting up big data environments with large up-front investments. Cloud computing seems to be a perfect vehicle for hosting big data workloads. However, working on big data in the cloud brings its own challenge of reconciling two contradictory design principles. Cloud computing is based on the concepts of consolidation and resource pooling, but big data systems (such as Hadoop) are built on the shared nothing principle, where each node is independent and self-sufficient. A solution architecture that can allow these mutually exclusive principles to coexist is required to truly exploit the elasticity and ease-of-use of cloud computing for big data environments. This IBM® RedpaperTM publication is aimed at chief architects, line-of-business executives, and CIOs to provide an understanding of the cloud-related challenges they face and give prescriptive guidance for how to realize the benefits of big data solutions quickly and cost-effectively.

R for Business Analytics

Author : A Ohri
Publisher : Springer Science & Business Media
ISBN 13 : 1461443431
Total Pages : 320 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis R for Business Analytics by : A Ohri

Download or read book R for Business Analytics written by A Ohri and published by Springer Science & Business Media. This book was released on 2012-09-14 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. The book utilizes Albert Einstein’s famous remarks on making things as simple as possible, but no simpler. This book will blow the last remaining doubts in your mind about using R in your business environment. Even non-technical users will enjoy the easy-to-use examples. The interviews with creators and corporate users of R make the book very readable. The author firmly believes Isaac Asimov was a better writer in spreading science than any textbook or journal author.

Essentials of Business Analytics

Author : Bhimasankaram Pochiraju
Publisher : Springer
ISBN 13 : 3319688375
Total Pages : 971 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Essentials of Business Analytics by : Bhimasankaram Pochiraju

Download or read book Essentials of Business Analytics written by Bhimasankaram Pochiraju and published by Springer. This book was released on 2019-07-10 with total page 971 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters. The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text. Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter.

Introducing Microsoft SQL Server 2019

Author : Kellyn Gorman
Publisher : Packt Publishing Ltd
ISBN 13 : 1838829822
Total Pages : 489 pages
Book Rating : 4.8/5 (388 download)

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Book Synopsis Introducing Microsoft SQL Server 2019 by : Kellyn Gorman

Download or read book Introducing Microsoft SQL Server 2019 written by Kellyn Gorman and published by Packt Publishing Ltd. This book was released on 2020-04-27 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the impressive storage and analytic tools available with the in-cloud and on-premises versions of Microsoft SQL Server 2019. Key FeaturesGain insights into what’s new in SQL Server 2019Understand use cases and customer scenarios that can be implemented with SQL Server 2019Discover new cross-platform tools that simplify management and analysisBook Description Microsoft SQL Server comes equipped with industry-leading features and the best online transaction processing capabilities. If you are looking to work with data processing and management, getting up to speed with Microsoft Server 2019 is key. Introducing SQL Server 2019 takes you through the latest features in SQL Server 2019 and their importance. You will learn to unlock faster querying speeds and understand how to leverage the new and improved security features to build robust data management solutions. Further chapters will assist you with integrating, managing, and analyzing all data, including relational, NoSQL, and unstructured big data using SQL Server 2019. Dedicated sections in the book will also demonstrate how you can use SQL Server 2019 to leverage data processing platforms, such as Apache Hadoop and Spark, and containerization technologies like Docker and Kubernetes to control your data and efficiently monitor it. By the end of this book, you'll be well versed with all the features of Microsoft SQL Server 2019 and understand how to use them confidently to build robust data management solutions. What you will learnBuild a custom container image with a DockerfileDeploy and run the SQL Server 2019 container imageUnderstand how to use SQL server on LinuxMigrate existing paginated reports to Power BI Report ServerLearn to query Hadoop Distributed File System (HDFS) data using Azure Data StudioUnderstand the benefits of In-Memory OLTPWho this book is for This book is for database administrators, architects, big data engineers, or anyone who has experience with SQL Server and wants to explore and implement the new features in SQL Server 2019. Basic working knowledge of SQL Server and relational database management system (RDBMS) is required.