Big Data At Work
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Big Data At Work
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Author : Thomas Davenport
language : en
Publisher: Harvard Business Review Press
Release Date : 2014-02-25
Big Data At Work written by Thomas Davenport and has been published by Harvard Business Review Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-25 with Business & Economics categories.
Go ahead, be skeptical about big data. The author was—at first. When the term “big data” first came on the scene, bestselling author Tom Davenport (Competing on Analytics, Analytics at Work) thought it was just another example of technology hype. But his research in the years that followed changed his mind. Now, in clear, conversational language, Davenport explains what big data means—and why everyone in business needs to know about it. Big Data at Work covers all the bases: what big data means from a technical, consumer, and management perspective; what its opportunities and costs are; where it can have real business impact; and which aspects of this hot topic have been oversold. This book will help you understand: • Why big data is important to you and your organization • What technology you need to manage it • How big data could change your job, your company, and your industry • How to hire, rent, or develop the kinds of people who make big data work • The key success factors in implementing any big data project • How big data is leading to a new approach to managing analytics With dozens of company examples, including UPS, GE, Amazon, United Healthcare, Citigroup, and many others, this book will help you seize all opportunities—from improving decisions, products, and services to strengthening customer relationships. It will show you how to put big data to work in your own organization so that you too can harness the power of this ever-evolving new resource.
Big Data
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Author : Viktor Mayer-Schönberger
language : en
Publisher: Houghton Mifflin Harcourt
Release Date : 2013
Big Data written by Viktor Mayer-Schönberger and has been published by Houghton Mifflin Harcourt this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Business & Economics categories.
A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large.
Analytics And Big Data The Davenport Collection 6 Items
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Author : Thomas H. Davenport
language : en
Publisher: Harvard Business Review Press
Release Date : 2014-08-12
Analytics And Big Data The Davenport Collection 6 Items written by Thomas H. Davenport and has been published by Harvard Business Review Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-12 with Business & Economics categories.
The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics.
Big Data At Work
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Author : Scott Tonidandel
language : en
Publisher: Routledge
Release Date : 2015-11-06
Big Data At Work written by Scott Tonidandel and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-06 with Psychology categories.
The amount of data in our world has been exploding, and analyzing large data sets—so called big data—will become a key basis of competition in business. Statisticians and researchers will be updating their analytic approaches, methods and research to meet the demands created by the availability of big data. The goal of this book is to show how advances in data science have the ability to fundamentally influence and improve organizational science and practice. This book is primarily designed for researchers and advanced undergraduate and graduate students in psychology, management and statistics.
Big Data At Work
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Author : Marlena Gaul
language : en
Publisher: CreateSpace
Release Date : 2014-11-26
Big Data At Work written by Marlena Gaul and has been published by CreateSpace this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-26 with categories.
Introduction Data warehousing is a success, judging by its 25 year history of use across all industries. Business intelligence met the needs it was designed for: to give non-technical people within the organization access to important, shared data. During the same period that data warehousing and BI matured, the automation and instrumenting of almost all processes and activities changed the data landscape in most companies. Where there were only a few applications and minimal monitoring 25 years ago, there is ubiquitous computing and data available about every activity today. Data warehouses have not been able to keep up with business demands for new sources of information, new types of data, more complex analysis and greater speed. Companies can put this data to use in countless ways, but for most it remains uncollected or unused, locked away in silos within IT. There has been a gradual maturing of data use in organizations. In the early days of BI it was enough to provide access to core financial and customer transactions. Better access enabled process changes, and these led to the need for more data and more varied uses of information. These changes put increasing strain on information processing and delivery capabilities that were designed under assumptions of stability and common use. Most companies now have a backlog of new data and analysis requests that BI groups are struggling to meet. Big data is not simply about growing data volumes - it's also about the fact that the data being collected today is different in ways that make it unwieldy for conventional databases and BI tools. Big data is also about new technologies that were developed to support the storage, retrieval and processing of this new data. The technologies originated in the world of web applications and internet-based companies, but they are now spreading into enterprise applications of all sorts. New technology coupled with new data enables new practices like real-time monitoring of operations across retail channels, supply chain practices at finer grain and faster speed, and analysis of customers at the level of individual activities and behaviors. Until recently, large scale data collection and analysis capabilities like these would have required a Wal-Mart sized investment, limiting them to large organizations. These capabilities are now available to all, regardless of company size or budget. This is creating a rush to adopt big data technologies. As the use of big data grows, the need for data management will grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. The combination of new data and new technology requires new data management capabilities and processes to capture the promised long-term value. Wal-Mart handles more than a million customer transactions each hour and imports those into databases estimated to contain more than 2.5 petabytes of data. Radio frequency identification (RFID) systems used by retailers and others can generate 100 to 1,000 times the data of conventional bar code systems. Facebook handles more than 250 million photo uploads and the interactions of 800 million active users with more than 900 million objects (pages, groups, etc.) - each day. More than 5 billion people are calling, texting, tweeting and browsing on mobile phones worldwide. Organizations are inundated with data - terabytes and petabytes of it. To put it in context, 1 terabyte contains 2,000 hours of CD-quality music and 10 terabytes could store the entire US Library of Congress print collection. Exabytes, zettabytes and yottabytes definitely are on the horizon . Data is pouring in from every conceivable direction: from operational and transactional systems, from scanning and facilities management systems, from inbound and outbound customer contact points, from mobile media and the Web .
Big Data Revolution
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Author : Rob Thomas
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-05
Big Data Revolution written by Rob Thomas and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-05 with Technology & Engineering categories.
Exploit the power and potential of Big Data to revolutionize business outcomes Big Data Revolution is a guide to improving performance, making better decisions, and transforming business through the effective use of Big Data. In this collaborative work by an IBM Vice President of Big Data Products and an Oxford Research Fellow, this book presents inside stories that demonstrate the power and potential of Big Data within the business realm. Readers are guided through tried-and-true methodologies for getting more out of data, and using it to the utmost advantage. This book describes the major trends emerging in the field, the pitfalls and triumphs being experienced, and the many considerations surrounding Big Data, all while guiding readers toward better decision making from the perspective of a data scientist. Companies are generating data faster than ever before, and managing that data has become a major challenge. With the right strategy, Big Data can be a powerful tool for creating effective business solutions – but deep understanding is key when applying it to individual business needs. Big Data Revolution provides the insight executives need to incorporate Big Data into a better business strategy, improving outcomes with innovation and efficient use of technology. Examine the major emerging patterns in Big Data Consider the debate surrounding the ethical use of data Recognize patterns and improve personal and organizational performance Make more informed decisions with quantifiable results In an information society, it is becoming increasingly important to make sense of data in an economically viable way. It can drive new revenue streams and give companies a competitive advantage, providing a way forward for businesses navigating an increasingly complex marketplace. Big Data Revolution provides expert insight on the tool that can revolutionize industries.
Big Data
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Author : Balamurugan Balusamy
language : en
Publisher: John Wiley & Sons
Release Date : 2021-03-03
Big Data written by Balamurugan Balusamy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-03 with Mathematics categories.
Learn Big Data from the ground up with this complete and up-to-date resource from leaders in the field Big Data: Concepts, Technology, and Architecture delivers a comprehensive treatment of Big Data tools, terminology, and technology perfectly suited to a wide range of business professionals, academic researchers, and students. Beginning with a fulsome overview of what we mean when we say, “Big Data,” the book moves on to discuss every stage of the lifecycle of Big Data. You’ll learn about the creation of structured, unstructured, and semi-structured data, data storage solutions, traditional database solutions like SQL, data processing, data analytics, machine learning, and data mining. You’ll also discover how specific technologies like Apache Hadoop, SQOOP, and Flume work. Big Data also covers the central topic of big data visualization with Tableau, and you’ll learn how to create scatter plots, histograms, bar, line, and pie charts with that software. Accessibly organized, Big Data includes illuminating case studies throughout the material, showing you how the included concepts have been applied in real-world settings. Some of those concepts include: The common challenges facing big data technology and technologists, like data heterogeneity and incompleteness, data volume and velocity, storage limitations, and privacy concerns Relational and non-relational databases, like RDBMS, NoSQL, and NewSQL databases Virtualizing Big Data through encapsulation, partitioning, and isolating, as well as big data server virtualization Apache software, including Hadoop, Cassandra, Avro, Pig, Mahout, Oozie, and Hive The Big Data analytics lifecycle, including business case evaluation, data preparation, extraction, transformation, analysis, and visualization Perfect for data scientists, data engineers, and database managers, Big Data also belongs on the bookshelves of business intelligence analysts who are required to make decisions based on large volumes of information. Executives and managers who lead teams responsible for keeping or understanding large datasets will also benefit from this book.
Big Data For Dummies
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Author : Judith S. Hurwitz
language : en
Publisher: John Wiley & Sons
Release Date : 2013-04-02
Big Data For Dummies written by Judith S. Hurwitz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-02 with Computers categories.
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.
Making Big Data Work For Your Business
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Author : Sudhi Sinha
language : en
Publisher: Packt Publishing Ltd
Release Date : 2014-10-28
Making Big Data Work For Your Business written by Sudhi Sinha 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 2014-10-28 with Business & Economics categories.
If your are interested in the power of Big Data to drive improvement in your business, then this book will help you build and initiate a project for positive change.
Real Time Big Data Analytics
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Author : Sumit Gupta
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-02-26
Real Time Big Data Analytics written by Sumit Gupta 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 2016-02-26 with Computers categories.
Design, process, and analyze large sets of complex data in real time About This Book Get acquainted with transformations and database-level interactions, and ensure the reliability of messages processed using Storm Implement strategies to solve the challenges of real-time data processing Load datasets, build queries, and make recommendations using Spark SQL Who This Book Is For If you are a Big Data architect, developer, or a programmer who wants to develop applications/frameworks to implement real-time analytics using open source technologies, then this book is for you. What You Will Learn Explore big data technologies and frameworks Work through practical challenges and use cases of real-time analytics versus batch analytics Develop real-word use cases for processing and analyzing data in real-time using the programming paradigm of Apache Storm Handle and process real-time transactional data Optimize and tune Apache Storm for varied workloads and production deployments Process and stream data with Amazon Kinesis and Elastic MapReduce Perform interactive and exploratory data analytics using Spark SQL Develop common enterprise architectures/applications for real-time and batch analytics In Detail Enterprise has been striving hard to deal with the challenges of data arriving in real time or near real time. Although there are technologies such as Storm and Spark (and many more) that solve the challenges of real-time data, using the appropriate technology/framework for the right business use case is the key to success. This book provides you with the skills required to quickly design, implement and deploy your real-time analytics using real-world examples of big data use cases. From the beginning of the book, we will cover the basics of varied real-time data processing frameworks and technologies. We will discuss and explain the differences between batch and real-time processing in detail, and will also explore the techniques and programming concepts using Apache Storm. Moving on, we'll familiarize you with “Amazon Kinesis” for real-time data processing on cloud. We will further develop your understanding of real-time analytics through a comprehensive review of Apache Spark along with the high-level architecture and the building blocks of a Spark program. You will learn how to transform your data, get an output from transformations, and persist your results using Spark RDDs, using an interface called Spark SQL to work with Spark. At the end of this book, we will introduce Spark Streaming, the streaming library of Spark, and will walk you through the emerging Lambda Architecture (LA), which provides a hybrid platform for big data processing by combining real-time and precomputed batch data to provide a near real-time view of incoming data. Style and approach This step-by-step is an easy-to-follow, detailed tutorial, filled with practical examples of basic and advanced features. Each topic is explained sequentially and supported by real-world examples and executable code snippets.