Hadoop Security

Protecting Your Big Data Platform

Author: Ben Spivey,Joey Echeverria

Publisher: "O'Reilly Media, Inc."

ISBN: 1491901349

Category: Computers

Page: 340

View: 5496

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As more corporations turn to Hadoop to store and process their most valuable data, the risk of a potential breach of those systems increases exponentially. This practical book not only shows Hadoop administrators and security architects how to protect Hadoop data from unauthorized access, it also shows how to limit the ability of an attacker to corrupt or modify data in the event of a security breach. Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. You’ll also get real-world examples that demonstrate how you can apply these concepts to your use cases. Understand the challenges of securing distributed systems, particularly Hadoop Use best practices for preparing Hadoop cluster hardware as securely as possible Get an overview of the Kerberos network authentication protocol Delve into authorization and accounting principles as they apply to Hadoop Learn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at rest Integrate Hadoop data ingest into enterprise-wide security architecture Ensure that security architecture reaches all the way to end-user access

Hadoop Security

Protecting Your Big Data Platform

Author: Ben Spivey,Joey Echeverria

Publisher: "O'Reilly Media, Inc."

ISBN: 1491900962

Category: Computers

Page: 340

View: 8852

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As more corporations turn to Hadoop to store and process their most valuable data, the risk of a potential breach of those systems increases exponentially. This practical book not only shows Hadoop administrators and security architects how to protect Hadoop data from unauthorized access, it also shows how to limit the ability of an attacker to corrupt or modify data in the event of a security breach. Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. You’ll also get real-world examples that demonstrate how you can apply these concepts to your use cases. Understand the challenges of securing distributed systems, particularly Hadoop Use best practices for preparing Hadoop cluster hardware as securely as possible Get an overview of the Kerberos network authentication protocol Delve into authorization and accounting principles as they apply to Hadoop Learn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at rest Integrate Hadoop data ingest into enterprise-wide security architecture Ensure that security architecture reaches all the way to end-user access

Hadoop Security

Protecting Your Big Data Platform

Author: Ben Spivey,Joey Echeverria

Publisher: Oreilly & Associates Incorporated

ISBN: 9781491900987

Category: Computers

Page: 330

View: 6998

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As more corporations turn to Hadoop to store and process their most valuable data, the risks with a potential breach of those systems increases exponentially. This practical book not only shows security architects how to protect Hadoop data from unauthorized access, but also how to limit the ability of an attacker to corrupt or modify data in the event of a security breach. Security is typically the longest phase of any Hadoop project. In this book, Cloudera professionals Ben Spivey and Joey Echeverria provide a thorough treatment of Hadoop security architecture and implementation to help architects navigate the common challenges of this phase. Example case studies demonstrate how the book’s material is immediately applicable to your use cases. Understand the challenges of securing distributed systems, particularly Hadoop Use best practices for preparing Hadoop cluster hardware from a security standpoint Get an overview of the Kerberos network authentication protocol Delve into authorization and accounting principles as they apply to Hadoop Use mechanisms to protect data in a Hadoop cluster, both in transit and at rest Integrate Hadoop data ingest into enterprise-wide security architecture Ensure that security architecture reaches all the way to end-user access

Practical Hadoop Security

Author: Bhushan Lakhe

Publisher: Apress

ISBN: 1430265450

Category: Computers

Page: 220

View: 7627

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Practical Hadoop Security is an excellent resource for administrators planning a production Hadoop deployment who want to secure their Hadoop clusters. A detailed guide to the security options and configuration within Hadoop itself, author Bhushan Lakhe takes you through a comprehensive study of how to implement defined security within a Hadoop cluster in a hands-on way. You will start with a detailed overview of all the security options available for Hadoop, including popular extensions like Kerberos and OpenSSH, and then delve into a hands-on implementation of user security (with illustrated code samples) with both in-the-box features and with security extensions implemented by leading vendors. No security system is complete without a monitoring and tracing facility, so Practical Hadoop Security next steps you through audit logging and monitoring technologies for Hadoop, as well as ready to use implementation and configuration examples--again with illustrated code samples. The book concludes with the most important aspect of Hadoop security – encryption. Both types of encryptions, for data in transit and data at rest, are discussed at length with leading open source projects that integrate directly with Hadoop at no licensing cost. Practical Hadoop Security: Explains importance of security, auditing and encryption within a Hadoop installation Describes how the leading players have incorporated these features within their Hadoop distributions and provided extensions Demonstrates how to set up and use these features to your benefit and make your Hadoop installation secure without impacting performance or ease of use

Securing Hadoop

Author: Sudheesh Narayanan

Publisher: Packt Publishing Ltd

ISBN: 1783285265

Category: Computers

Page: 116

View: 8158

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This book is a step-by-step tutorial filled with practical examples which will focus mainly on the key security tools and implementation techniques of Hadoop security.This book is great for Hadoop practitioners (solution architects, Hadoop administrators, developers, and Hadoop project managers) who are looking to get a good grounding in what Kerberos is all about and who wish to learn how to implement end-to-end Hadoop security within an enterprise setup. It’s assumed that you will have some basic understanding of Hadoop as well as be familiar with some basic security concepts.

Modern Big Data Processing with Hadoop

Expert techniques for architecting end-to-end big data solutions to get valuable insights

Author: V Naresh Kumar,Prashant Shindgikar

Publisher: Packt Publishing Ltd

ISBN: 1787128814

Category: Computers

Page: 394

View: 7425

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A comprehensive guide to design, build and execute effective Big Data strategies using Hadoop Key Features -Get an in-depth view of the Apache Hadoop ecosystem and an overview of the architectural patterns pertaining to the popular Big Data platform -Conquer different data processing and analytics challenges using a multitude of tools such as Apache Spark, Elasticsearch, Tableau and more -A comprehensive, step-by-step guide that will teach you everything you need to know, to be an expert Hadoop Architect Book Description The complex structure of data these days requires sophisticated solutions for data transformation, to make the information more accessible to the users.This book empowers you to build such solutions with relative ease with the help of Apache Hadoop, along with a host of other Big Data tools. This book will give you a complete understanding of the data lifecycle management with Hadoop, followed by modeling of structured and unstructured data in Hadoop. It will also show you how to design real-time streaming pipelines by leveraging tools such as Apache Spark, and build efficient enterprise search solutions using Elasticsearch. You will learn to build enterprise-grade analytics solutions on Hadoop, and how to visualize your data using tools such as Apache Superset. This book also covers techniques for deploying your Big Data solutions on the cloud Apache Ambari, as well as expert techniques for managing and administering your Hadoop cluster. By the end of this book, you will have all the knowledge you need to build expert Big Data systems. What you will learn Build an efficient enterprise Big Data strategy centered around Apache Hadoop Gain a thorough understanding of using Hadoop with various Big Data frameworks such as Apache Spark, Elasticsearch and more Set up and deploy your Big Data environment on premises or on the cloud with Apache Ambari Design effective streaming data pipelines and build your own enterprise search solutions Utilize the historical data to build your analytics solutions and visualize them using popular tools such as Apache Superset Plan, set up and administer your Hadoop cluster efficiently Who this book is for This book is for Big Data professionals who want to fast-track their career in the Hadoop industry and become an expert Big Data architect. Project managers and mainframe professionals looking forward to build a career in Big Data Hadoop will also find this book to be useful. Some understanding of Hadoop is required to get the best out of this book.

Expert Hadoop Administration

Managing, Tuning, and Securing Spark, YARN, and HDFS

Author: Sam R. Alapati

Publisher: Addison-Wesley Professional

ISBN: 0134703383

Category: Computers

Page: 848

View: 6938

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This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. The Comprehensive, Up-to-Date Apache Hadoop Administration Handbook and Reference “Sam Alapati has worked with production Hadoop clusters for six years. His unique depth of experience has enabled him to write the go-to resource for all administrators looking to spec, size, expand, and secure production Hadoop clusters of any size.” —Paul Dix, Series Editor In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples. Alapati demystifies complex Hadoop environments, helping you understand exactly what happens behind the scenes when you administer your cluster. You’ll gain unprecedented insight as you walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes. The high-value administration skills you learn here will be indispensable no matter what Hadoop distribution you use or what Hadoop applications you run. Understand Hadoop’s architecture from an administrator’s standpoint Create simple and fully distributed clusters Run MapReduce and Spark applications in a Hadoop cluster Manage and protect Hadoop data and high availability Work with HDFS commands, file permissions, and storage management Move data, and use YARN to allocate resources and schedule jobs Manage job workflows with Oozie and Hue Secure, monitor, log, and optimize Hadoop Benchmark and troubleshoot Hadoop

Scaling Big Data with Hadoop and Solr

Author: Hrishikesh Karambelkar

Publisher: Packt Publishing Ltd

ISBN: 1783281383

Category: Computers

Page: 144

View: 1156

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This book is a step-by-step tutorial that will enable you to leverage the flexible search functionality of Apache Solr together with the Big Data power of Apache Hadoop.Scaling Big Data with Hadoop and Solr provides guidance to developers who wish to build high-speed enterprise search platforms using Hadoop and Solr. This book is primarily aimed at Java programmers who wish to extend the Hadoop platform to make it run as an enterprise search without any prior knowledge of Apache Hadoop and Solr.

Hadoop Operations

A Guide for Developers and Administrators

Author: Eric Sammer

Publisher: "O'Reilly Media, Inc."

ISBN: 144932729X

Category: Computers

Page: 298

View: 560

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If you’ve been asked to maintain large and complex Hadoop clusters, this book is a must. Demand for operations-specific material has skyrocketed now that Hadoop is becoming the de facto standard for truly large-scale data processing in the data center. Eric Sammer, Principal Solution Architect at Cloudera, shows you the particulars of running Hadoop in production, from planning, installing, and configuring the system to providing ongoing maintenance. Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments. Get a high-level overview of HDFS and MapReduce: why they exist and how they work Plan a Hadoop deployment, from hardware and OS selection to network requirements Learn setup and configuration details with a list of critical properties Manage resources by sharing a cluster across multiple groups Get a runbook of the most common cluster maintenance tasks Monitor Hadoop clusters—and learn troubleshooting with the help of real-world war stories Use basic tools and techniques to handle backup and catastrophic failure

Kerberos

The Definitive Guide

Author: Jason Garman

Publisher: "O'Reilly Media, Inc."

ISBN: 0596004036

Category: Computers

Page: 253

View: 4481

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Kerberos, the single sign-on authentication system originally developed at MIT, deserves its name. It's a faithful watchdog that keeps intruders out of your networks. But it has been equally fierce to system administrators, for whom the complexity of Kerberos is legendary. Single sign-on is the holy grail of network administration, and Kerberos is the only game in town. Microsoft, by integrating Kerberos into Active Directory in Windows 2000 and 2003, has extended the reach of Kerberos to all networks large or small. Kerberos makes your network more secure and more convenient for users by providing a single authentication system that works across the entire network. One username; one password; one login is all you need. Fortunately, help for administrators is on the way. Kerberos: The Definitive Guide shows you how to implement Kerberos for secure authentication. In addition to covering the basic principles behind cryptographic authentication, it covers everything from basic installation to advanced topics like cross-realm authentication, defending against attacks on Kerberos, and troubleshooting. In addition to covering Microsoft's Active Directory implementation, Kerberos: The Definitive Guide covers both major implementations of Kerberos for Unix and Linux: MIT and Heimdal. It shows you how to set up Mac OS X as a Kerberos client. The book also covers both versions of the Kerberos protocol that are still in use: Kerberos 4 (now obsolete) and Kerberos 5, paying special attention to the integration between the different protocols, and between Unix and Windows implementations. If you've been avoiding Kerberos because it's confusing and poorly documented, it's time to get on board! This book shows you how to put Kerberos authentication to work on your Windows and Unix systems.

Data Lake Development with Big Data

Author: Pradeep Pasupuleti,Beulah Salome Purra

Publisher: Packt Publishing Ltd

ISBN: 1785881663

Category: Computers

Page: 164

View: 9395

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Explore architectural approaches to building Data Lakes that ingest, index, manage, and analyze massive amounts of data using Big Data technologies About This Book Comprehend the intricacies of architecting a Data Lake and build a data strategy around your current data architecture Efficiently manage vast amounts of data and deliver it to multiple applications and systems with a high degree of performance and scalability Packed with industry best practices and use-case scenarios to get you up-and-running Who This Book Is For This book is for architects and senior managers who are responsible for building a strategy around their current data architecture, helping them identify the need for a Data Lake implementation in an enterprise context. The reader will need a good knowledge of master data management and information lifecycle management, and experience of Big Data technologies. What You Will Learn Identify the need for a Data Lake in your enterprise context and learn to architect a Data Lake Learn to build various tiers of a Data Lake, such as data intake, management, consumption, and governance, with a focus on practical implementation scenarios Find out the key considerations to be taken into account while building each tier of the Data Lake Understand Hadoop-oriented data transfer mechanism to ingest data in batch, micro-batch, and real-time modes Explore various data integration needs and learn how to perform data enrichment and data transformations using Big Data technologies Enable data discovery on the Data Lake to allow users to discover the data Discover how data is packaged and provisioned for consumption Comprehend the importance of including data governance disciplines while building a Data Lake In Detail A Data Lake is a highly scalable platform for storing huge volumes of multistructured data from disparate sources with centralized data management services. This book explores the potential of Data Lakes and explores architectural approaches to building data lakes that ingest, index, manage, and analyze massive amounts of data using batch and real-time processing frameworks. It guides you on how to go about building a Data Lake that is managed by Hadoop and accessed as required by other Big Data applications. This book will guide readers (using best practices) in developing Data Lake's capabilities. It will focus on architect data governance, security, data quality, data lineage tracking, metadata management, and semantic data tagging. By the end of this book, you will have a good understanding of building a Data Lake for Big Data. Style and approach Data Lake Development with Big Data provides architectural approaches to building a Data Lake. It follows a use case-based approach where practical implementation scenarios of each key component are explained. It also helps you understand how these use cases are implemented in a Data Lake. The chapters are organized in a way that mimics the sequential data flow evidenced in a Data Lake.

Hadoop Essentials

Author: Shiva Achari

Publisher: Packt Publishing Ltd

ISBN: 1784390461

Category: Computers

Page: 194

View: 1870

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If you are a system or application developer interested in learning how to solve practical problems using the Hadoop framework, then this book is ideal for you. This book is also meant for Hadoop professionals who want to find solutions to the different challenges they come across in their Hadoop projects.

Microsoft Big Data Solutions

Author: Adam Jorgensen,James Rowland-Jones,John Welch,Dan Clark,Christopher Price,Brian Mitchell

Publisher: John Wiley & Sons

ISBN: 1118729552

Category: Computers

Page: 408

View: 6239

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Tap the power of Big Data with Microsoft technologies Big Data is here, and Microsoft's new Big Data platform is a valuable tool to help your company get the very most out of it. This timely book shows you how to use HDInsight along with HortonWorks Data Platform for Windows to store, manage, analyze, and share Big Data throughout the enterprise. Focusing primarily on Microsoft and HortonWorks technologies but also covering open source tools, Microsoft Big Data Solutions explains best practices, covers on-premises and cloud-based solutions, and features valuable case studies. Best of all, it helps you integrate these new solutions with technologies you already know, such as SQL Server and Hadoop. Walks you through how to integrate Big Data solutions in your company using Microsoft's HDInsight Server, HortonWorks Data Platform for Windows, and open source tools Explores both on-premises and cloud-based solutions Shows how to store, manage, analyze, and share Big Data through the enterprise Covers topics such as Microsoft's approach to Big Data, installing and configuring HortonWorks Data Platform for Windows, integrating Big Data with SQL Server, visualizing data with Microsoft and HortonWorks BI tools, and more Helps you build and execute a Big Data plan Includes contributions from the Microsoft and HortonWorks Big Data product teams If you need a detailed roadmap for designing and implementing a fully deployed Big Data solution, you'll want Microsoft Big Data Solutions.

Big Data Analytics with R

Author: Simon Walkowiak

Publisher: Packt Publishing Ltd

ISBN: 1786463725

Category: Computers

Page: 506

View: 6602

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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.

Java 9 Programming By Example

Author: Peter Verhas

Publisher: Packt Publishing Ltd

ISBN: 1786464519

Category: Computers

Page: 504

View: 5382

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Get the steps you need to discover the world of Java 9 programming using real-world examples About This Book We bridge the gap between “learning” and “doing” by providing real-world examples that will improve your software development Our example-based approach will get you started quickly with software programming, get you up-to-speed with Java 9, and improve your Java skills This book will show you the best practices of Java coding and improve your productivity Who This Book Is For This book is for anyone who wants to learn the Java programming language. You are expected to have some prior programming experience with another language, such as JavaScript or Python, but no knowledge of earlier versions of Java is assumed. What You Will Learn Compile, package and run a trivial program using a build management tool Get to know the principles of test-driven development and dependency management Separate the wiring of multiple modules from the application logic into an application using dependency injection Benchmark Java execution using Java 9 microbenchmarking See the workings of the Spring framework and use Java annotations for the configuration Master the scripting API built into the Java language and use the built-in JavaScript interpreter Understand static versus dynamic implementation of code and high-order reactive programming in Java In Detail This book gets you started with essential software development easily and quickly, guiding you through Java's different facets. By adopting this approach, you can bridge the gap between learning and doing immediately. You will learn the new features of Java 9 quickly and experience a simple and powerful approach to software development. You will be able to use the Java runtime tools, understand the Java environment, and create Java programs. We then cover more simple examples to build your foundation before diving to some complex data structure problems that will solidify your Java 9 skills. With a special focus on modularity and HTTP 2.0, this book will guide you to get employed as a top notch Java developer. By the end of the book, you will have a firm foundation to continue your journey towards becoming a professional Java developer. Style and approach Throughout this book, our aim is to build Java programs. We will be building multiple applications ranging from simpler ones to more complex ones. Learning by doing has its advantages as you will immediately see the concepts explained in action.

Harness the Power of Big Data The IBM Big Data Platform

Author: Paul Zikopoulos,Dirk deRoos,Krishnan Parasuraman,Thomas Deutsch,James Giles,David Corrigan

Publisher: McGraw Hill Professional

ISBN: 0071808183

Category: Computers

Page: 280

View: 6000

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Boost your Big Data IQ! Gain insight into how to govern and consume IBM’s unique in-motion and at-rest Big Data analytic capabilities Big Data represents a new era of computing—an inflection point of opportunity where data in any format may be explored and utilized for breakthrough insights—whether that data is in-place, in-motion, or at-rest. IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is infusing open source Big Data technologies with IBM innovation that manifest in a platform capable of "changing the game." The four defining characteristics of Big Data—volume, variety, velocity, and veracity—are discussed. You’ll understand how IBM is fully committed to Hadoop and integrating it into the enterprise. Hear about how organizations are taking inventories of their existing Big Data assets, with search capabilities that help organizations discover what they could already know, and extend their reach into new data territories for unprecedented model accuracy and discovery. In this book you will also learn not just about the technologies that make up the IBM Big Data platform, but when to leverage its purpose-built engines for analytics on data in-motion and data at-rest. And you’ll gain an understanding of how and when to govern Big Data, and how IBM’s industry-leading InfoSphere integration and governance portfolio helps you understand, govern, and effectively utilize Big Data. Industry use cases are also included in this practical guide.

Hadoop in the Enterprise - Architecture

A Guide to Successful Integration

Author: Jan Kunigk,Lars George,Ian Buss,Paul Wilkinson

Publisher: O'Reilly Media

ISBN: 9781491969274

Category: Computers

Page: 315

View: 5568

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This practical book provides a comprehensive guide on how to make enterprise Hadoop integration successful. You ll learn how to build a Hadoop infrastructure, architect an enterprise Hadoop platform, and even take Hadoop to the cloud. Ideal for engineers, technical and enterprise architects, and technical leads, this guide includes lots of practical examples that can be easily comprehended by technical architects, and put into practice by an engineer, developer, and/or cluster operator. "

Big Data For Dummies

Author: Judith Hurwitz,Alan Nugent,Fern Halper,Marcia Kaufman

Publisher: John Wiley & Sons

ISBN: 1118644174

Category: Computers

Page: 336

View: 2493

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Find the right big data solution for your business or organization Big data management is one of the major challenges facing business, industry, and not-for-profit organizations. Data sets such as customer transactions for a mega-retailer, weather patterns monitored by meteorologists, or social network activity can quickly outpace the capacity of traditional data management tools. If you need to develop or manage big data solutions, you'll appreciate how these four experts define, explain, and guide you through this new and often confusing concept. You'll learn what it is, why it matters, and how to choose and implement solutions that work. Effectively managing big data is an issue of growing importance to businesses, not-for-profit organizations, government, and IT professionals Authors are experts in information management, big data, and a variety of solutions Explains big data in detail and discusses how to select and implement a solution, security concerns to consider, data storage and presentation issues, analytics, and much more Provides essential information in a no-nonsense, easy-to-understand style that is empowering Big Data For Dummies cuts through the confusion and helps you take charge of big data solutions for your organization.

Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data

Author: Paul Zikopoulos,Chris Eaton

Publisher: McGraw Hill Professional

ISBN: 0071790543

Category: Computers

Page: 176

View: 1033

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Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer