Hadoop Integration In Ibm Microsoft And Sas
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Hadoop Integration In Ibm Microsoft And Sas
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Author : James Braselton
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2014-08-06
Hadoop Integration In Ibm Microsoft And Sas written by James Braselton and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-06 with Apache Hadoop categories.
There are mountains of untapped potential in our information. Until now, it's been too cost prohibitive to analyze these massive volumes. Of course, there's also been a staggering opportunity cost associated with not tapping into this information, as the potential of this yet-to-be-analyzed information is near-limitless. And we're not just talking the ubiquitous "competitive differentiation" marketing slogan here; we're talking innovation, discovery, association, and pretty much any- thing else that could make the way you work tomorrow very different, with even more tangible results and insight, from the way you work today. People and organizations have attempted to tackle this problem from many different angles. Of course, the angle that is currently leading the pack in terms of popularity for massive data analysis is an open source project called Hadoop. Hadoop is shipped as part of IBM tools, SQL Server 2014 and SAS applications. Hadoop is shipped as part of the IBM InfoSphere BigInsights (BigInsights) platform. Quite simply, BigInsights embraces, hardens, and extends the Hadoop open source framework with enterprise-grade security, governance, availability, integration into existing data stores, tooling that simplifies and improves developer productivity, scalability, analytic toolkits, and more. BigInsights is (and will always be) based on the nonforked core Hadoop distribution, and backwards compatibility. Hadoop is also shipped as part of SAS tools. SAS incorporated Hadoop into their applications (SAS Base, SAS Data Integration, Sas Enterpris Guide and SAS Enterprise Miner). Same SAS aplications works in-memory on Hadoop (In-memory Statistics, SAS Visual Analytics and SAS Visual Statistics). Finaly, Hadoop is also shipped as part of Microsoft SQL Server 2014 and HDInsight. SQL Server 2014 works in-memory across Hadoop. HDInsight is a Hadoop-based platform that you can use to process data of all kinds in the cloud. In particular, HDInsight is useful for processing high volumes of structured and unstructured data, which traditional relational database systems typically cannot support for a variety of reasons. HDInsight allows you to quickly establish an infrastructure for big data analysis, whether you want to develop a proof of concept for a big data solution or support ongoing analytical requirements in a production environment. Furthermore, HDInsight integrates with Microsoft's business-intelligence tools to enable users to enhance big data with additional sources and then explore and analyze the results to gain deeper insights. Most functionality within HDInsight and other Hadoop distributions is similar. Consequently, any current experience with Hadoop is largely transferable. Keep in mind that interaction with HDInsight requires you to use Windows Azure PowerShell commands, so a basic knowledge of PowerShell is required to work with the cluster.
Handbook Of Research On Strategic Performance Management And Measurement Using Data Envelopment Analysis
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Author : Osman, Ibrahim H.
language : en
Publisher: IGI Global
Release Date : 2013-08-31
Handbook Of Research On Strategic Performance Management And Measurement Using Data Envelopment Analysis written by Osman, Ibrahim H. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-31 with Business & Economics categories.
Organizations can use the valuable tool of data envelopment analysis (DEA) to make informed decisions on developing successful strategies, setting specific goals, and identifying underperforming activities to improve the output or outcome of performance measurement. The Handbook of Research on Strategic Performance Management and Measurement Using Data Envelopment Analysis highlights the advantages of using DEA as a tool to improve business performance and identify sources of inefficiency in public and private organizations. These recently developed theories and applications of DEA will be useful for policymakers, managers, and practitioners in the areas of sustainable development of our society including environment, agriculture, finance, and higher education sectors.
Hadoop Blueprints
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Author : Anurag Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-09-30
Hadoop Blueprints written by Anurag Shrivastava and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-30 with Computers categories.
Use Hadoop to solve business problems by learning from a rich set of real-life case studies About This Book Solve real-world business problems using Hadoop and other Big Data technologies Build efficient data lakes in Hadoop, and develop systems for various business cases like improving marketing campaigns, fraud detection, and more Power packed with six case studies to get you going with Hadoop for Business Intelligence Who This Book Is For If you are interested in building efficient business solutions using Hadoop, this is the book for you This book assumes that you have basic knowledge of Hadoop, Java, and any scripting language. What You Will Learn Learn about the evolution of Hadoop as the big data platform Understand the basics of Hadoop architecture Build a 360 degree view of your customer using Sqoop and Hive Build and run classification models on Hadoop using BigML Use Spark and Hadoop to build a fraud detection system Develop a churn detection system using Java and MapReduce Build an IoT-based data collection and visualization system Get to grips with building a Hadoop-based Data Lake for large enterprises Learn about the coexistence of NoSQL and In-Memory databases in the Hadoop ecosystem In Detail If you have a basic understanding of Hadoop and want to put your knowledge to use to build fantastic Big Data solutions for business, then this book is for you. Build six real-life, end-to-end solutions using the tools in the Hadoop ecosystem, and take your knowledge of Hadoop to the next level. Start off by understanding various business problems which can be solved using Hadoop. You will also get acquainted with the common architectural patterns which are used to build Hadoop-based solutions. Build a 360-degree view of the customer by working with different types of data, and build an efficient fraud detection system for a financial institution. You will also develop a system in Hadoop to improve the effectiveness of marketing campaigns. Build a churn detection system for a telecom company, develop an Internet of Things (IoT) system to monitor the environment in a factory, and build a data lake – all making use of the concepts and techniques mentioned in this book. The book covers other technologies and frameworks like Apache Spark, Hive, Sqoop, and more, and how they can be used in conjunction with Hadoop. You will be able to try out the solutions explained in the book and use the knowledge gained to extend them further in your own problem space. Style and approach This is an example-driven book where each chapter covers a single business problem and describes its solution by explaining the structure of a dataset and tools required to process it. Every project is demonstrated with a step-by-step approach, and explained in a very easy-to-understand manner.
Supporting Investment In Knowledge Capital Growth And Innovation
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Author : OECD
language : en
Publisher: OECD Publishing
Release Date : 2013-10-10
Supporting Investment In Knowledge Capital Growth And Innovation written by OECD and has been published by OECD Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-10 with categories.
This work shows that business investment in knowledge-based capital is a key to future productivity growth and living standards and sets out recommendations in the fields of: innovation; taxation; entrepreneurship and business development; corporate reporting; big data; competition and measurement.
Research Methods For Political Science
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Author : David E. McNabb
language : en
Publisher: Routledge
Release Date : 2020-12-31
Research Methods For Political Science written by David E. McNabb and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-31 with Education categories.
The third edition of Research Methods for Political Science retains its effective approach to helping students learn what to research, why to research and how to research. The text integrates both quantitative and qualitative approaches to research in one volume and covers such important topics as research design, specifying research problems, designing questionnaires and writing questions, designing and carrying out qualitative research and analyzing both quantitative and qualitative research data. Heavily illustrated, classroom tested, exceptionally readable and engaging, the text presents statistical methods in a conversational tone to help students surmount "math phobia." Updates to this new edition include: Research topics chapters have been upgraded and expanded. Two mixed methods design chapters have been added. A new chapter on hermeneutic analysis designs and research with large data sets. The chapter on multivariate statistics has been expanded, with an expanded discussion on logistic regression. Tools on how to prepare and present research findings are now featured in the appendix, allowing instructors more flexibility when teaching their courses. Research Methods for Political Science will give students the confidence and knowledge they need to understand the methods and basics skills for data collection, presentation and analysis.
Data Driven Innovation Big Data For Growth And Well Being
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Author : OECD
language : en
Publisher: OECD Publishing
Release Date : 2015-10-06
Data Driven Innovation Big Data For Growth And Well Being written by OECD and has been published by OECD Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-06 with categories.
This report improves the evidence base on the role of Data Driven Innovation for promoting growth and well-being, and provide policy guidance on how to maximise the benefits of DDI and mitigate the associated economic and societal risks.
Future Trends Of Hpc In A Disruptive Scenario
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Author : L. Grandinetti
language : en
Publisher: IOS Press
Release Date : 2019-09-27
Future Trends Of Hpc In A Disruptive Scenario written by L. Grandinetti and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-27 with Computers categories.
The realization that the use of components off the shelf (COTS) could reduce costs sparked the evolution of the massive parallel computing systems available today. The main problem with such systems is the development of suitable operating systems, algorithms and application software that can utilise the potential processing power of large numbers of processors. As a result, systems comprising millions of processors are still limited in the applications they can efficiently solve. Two alternative paradigms that may offer a solution to this problem are Quantum Computers (QC) and Brain Inspired Computers (BIC). This book presents papers from the 14th edition of the biennial international conference on High Performance Computing - From Clouds and Big Data to Exascale and Beyond, held in Cetraro, Italy, from 2 - 6 July 2018. It is divided into 4 sections covering data science, quantum computing, high-performance computing, and applications. The papers presented during the workshop covered a wide spectrum of topics on new developments in the rapidly evolving supercomputing field – including QC and BIC – and a selection of contributions presented at the workshop are included in this volume. In addition, two papers presented at a workshop on Brain Inspired Computing in 2017 and an overview of work related to data science executed by a number of universities in the USA, parts of which were presented at the 2018 and previous workshops, are also included. The book will be of interest to all those whose work involves high-performance computing.
Practical Hadoop Migration
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Author : Bhushan Lakhe
language : en
Publisher: Apress
Release Date : 2016-08-10
Practical Hadoop Migration written by Bhushan Lakhe and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-10 with Computers categories.
Re-architect relational applications to NoSQL, integrate relational database management systems with the Hadoop ecosystem, and transform and migrate relational data to and from Hadoop components. This book covers the best-practice design approaches to re-architecting your relational applications and transforming your relational data to optimize concurrency, security, denormalization, and performance. Winner of IBM’s 2012 Gerstner Award for his implementation of big data and data warehouse initiatives and author of Practical Hadoop Security, author Bhushan Lakhe walks you through the entire transition process. First, he lays out the criteria for deciding what blend of re-architecting, migration, and integration between RDBMS and HDFS best meets your transition objectives. Then he demonstrates how to design your transition model. Lakhe proceeds to cover the selection criteria for ETL tools, the implementation steps for migration with SQOOP- and Flume-based data transfers, and transition optimization techniques for tuning partitions, scheduling aggregations, and redesigning ETL. Finally, he assesses the pros and cons of data lakes and Lambda architecture as integrative solutions and illustrates their implementation with real-world case studies. Hadoop/NoSQL solutions do not offer by default certain relational technology features such as role-based access control, locking for concurrent updates, and various tools for measuring and enhancing performance. Practical Hadoop Migration shows how to use open-source tools to emulate such relational functionalities in Hadoop ecosystem components. What You'll Learn Decide whether you should migrate your relational applications to big data technologies or integrate them Transition your relational applications to Hadoop/NoSQL platforms in terms of logical design and physical implementation Discover RDBMS-to-HDFS integration, data transformation, and optimization techniques Consider when to use Lambda architecture and data lake solutions Select and implement Hadoop-based components and applications to speed transition, optimize integrated performance, and emulate relational functionalities Who This Book Is For Database developers, database administrators, enterprise architects, Hadoop/NoSQL developers, and IT leaders. Its secondary readership is project and program managers and advanced students of database and management information systems.
Big Data T Cnicas Herramientas Y Aplicaciones
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Author : María PÉREZ MARQUÉS
language : es
Publisher: Alfaomega Grupo Editor
Release Date : 2015-07-24
Big Data T Cnicas Herramientas Y Aplicaciones written by María PÉREZ MARQUÉS and has been published by Alfaomega Grupo Editor this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-24 with Business & Economics categories.
En la era de grandes conjuntos de datos, procedentes de diversos orígenes, en formatos variados y con una necesidad de procesamiento y análisis rápido y efectivo, las técnicas de Big Data persiguen complementar el manejo ordenado de estos volúmenes, con las técnicas de análisis de la información más avanzadas y efectivas para extraer de modo óptimo el conocimiento contenido en los datos. Las herramientas de Big Data se basan en el paquete de código abierto llamado Hadoop para el análisis masivo de datos, que forma parte de prácticamente todo el software de Big Data. Por ejemplo, SAS incorpora Hadoop en sus aplicaciones (SAS Base, SAS Data Integration, SAS Visual Analytics, SAS Visual Statistics, etc.). IBM trabaja con Hadoop en su plataforma IBM InfoSphere BigInsights. Microsoft incluye Hadoop en su plataforma Windows Azure, SQL Server 2014, HDInsight y Polybase. Oracle incluye Hadoop en Oracle Big Data Appliance, Oracle Big Data Connectors y Oracle Loader for Hadoop. Se describen y analizan estas herramientas de Big Data que implementan SAS, IBM, Microsoft y Oracle, para extraer el conocimiento contenido en los datos. Ventajas: · Los principales comandos Conozca: · Las herramientas de BIG DATA, que utilizan tecnologías multinúcleo para ofrecer mayor capacidad de procesamiento a través de altas prestaciones, en base de datos y de análisis en memoria que ofrecen un mayor conocimiento más rápidamente de grandes volúmenes de datos y flujo de datos, independientemente de los formatos y las fuentes de los orígenes de datos. Aprenda: ·Que con las herramientas de BIG DATA se puede procesar información online proveniente de múltiples orígenes (redes sociales o grandes bases de datos no estructuradas), · A tratar los datos de múltiples fuentes y formatos, ya sean texto, datos, imágenes o mezcla de todo ello. Actualmente es posible. Desarrolle sus habilidades para: · Implementar herramientas de BIG DATA en la forma que mejor se adapte a las necesidades de los usuarios. · Superar con éxito el desafío del análisis de la información, dada la capacidad de almacenar cualquier cosa, lo que están generando datos como nunca antes en la historia
Applications Of Big Data Analytics
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Author : Mohammed M. Alani
language : en
Publisher: Springer
Release Date : 2018-07-23
Applications Of Big Data Analytics written by Mohammed M. Alani and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-23 with Computers categories.
This timely text/reference reviews the state of the art of big data analytics, with a particular focus on practical applications. An authoritative selection of leading international researchers present detailed analyses of existing trends for storing and analyzing big data, together with valuable insights into the challenges inherent in current approaches and systems. This is further supported by real-world examples drawn from a broad range of application areas, including healthcare, education, and disaster management. The text also covers, typically from an application-oriented perspective, advances in data science in such areas as big data collection, searching, analysis, and knowledge discovery. Topics and features: Discusses a model for data traffic aggregation in 5G cellular networks, and a novel scheme for resource allocation in 5G networks with network slicing Explores methods that use big data in the assessment of flood risks, and apply neural networks techniques to monitor the safety of nuclear power plants Describes a system which leverages big data analytics and the Internet of Things in the application of drones to aid victims in disaster scenarios Proposes a novel deep learning-based health data analytics application for sleep apnea detection, and a novel pathway for diagnostic models of headache disorders Reviews techniques for educational data mining and learning analytics, and introduces a scalable MapReduce graph partitioning approach for high degree vertices Presents a multivariate and dynamic data representation model for the visualization of healthcare data, and big data analytics methods for software reliability assessment This practically-focused volume is an invaluable resource for all researchers, academics, data scientists and business professionals involved in the planning, designing, and implementation of big data analytics projects. Dr. Mohammed M. Alani is an Associate Professor in Computer Engineering and currently is the Provost at Al Khawarizmi International College, Abu Dhabi, UAE. Dr. Hissam Tawfik is a Professor of Computer Science in the School of Computing, Creative Technologies & Engineering at Leeds Beckett University, UK. Dr. Mohammed Saeed is a Professor in Computing and currently is the Vice President for Academic Affairs and Research at the University of Modern Sciences, Dubai, UAE. Dr. Obinna Anya is a Research Staff Member at IBM Research – Almaden, San Jose, CA, USA.