Big Data Fujitsu Global

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THE WHITE BOOK OF , Big, Data, The definitive guide to the. revolution in business analytics, THE WHITE,BOOK OF . Big Data,Contents,Acknowledgements 4 ,Preface 5,1 What is Big Data 6. 2 What does Big Data Mean for the Business 16,3 Clearing Big Data Hurdles 24. 4 Adoption Approaches 32,5 Changing Role of the Executive Team 42.
6 Rise of the Data Scientist 46,7 The Future of Big Data 48. 8 The Final Word on Big Data 52,Big Data Speak Key terms explained 57. Appendix The White Book Series 60, Acknowledgements. With thanks to our authors ,l Ian Mitchell Chief Architect UK Ireland Fujitsu. l Mark Locke Head of Planning Architecture International Business Fujitsu. l Mark Wilson Strategy Manager UK Ireland Fujitsu, l Andy Fuller Big Data Offering Manager UK Ireland Fujitsu.
With further thanks to colleagues at Fujitsu in Australia Europe and Japan who kindly. reviewed the book s contents and provided invaluable feedback . For more information on Fujitsu s Big Data capabilities and to learn how we can assist your. organisation further please contact us at askfujitsu uk fujitsu com or contact your local. Fujitsu team see page 62 ,ISBN 978 0 9568216 2 1,Published by Fujitsu Services Ltd . Copyright Fujitsu Services Ltd 2012 All rights reserved . No part of this document may be reproduced stored or transmitted in any form without prior written. permission of Fujitsu Services Ltd Fujitsu Services Ltd endeavours to ensure that the information in. this document is correct and fairly stated but does not accept liability for any errors or omissions . Preface, In economically uncertain times many businesses and public sector. organisations have come to appreciate that the key to better decisions more. effective customer citizen engagement sharper competitive edge hyper . efficient operations and compelling product and service development is. data and lots of it Today the situation they face is not any shortage of. that raw material the wealth of unstructured online data alone has swollen. the already torrential flow from transaction systems and demographic. sources but how to turn that amorphous vast fast flowing mass of Big. Data into highly valuable insights actions and outcomes . This Fujitsu White Book of Big Data aims to cut through a lot of the market. hype surrounding the subject to clearly define the challenges and. opportunities that organisations face as they seek to exploit Big Data . Written for both an IT and wider executive audience it explores the different. approaches to Big Data adoption the issues that can hamper Big Data. initiatives and the new skillsets that will be required by both IT specialists. and management to deliver success At a fundamental level it also shows. how to map business priorities onto an action plan for turning Big Data into. increased revenues and lower costs , At Fujitsu we have an even broader and more comprehensive vision for. Big Data as it intersects with the other megatrends in IT cloud and. mobility Our Cloud Fusion innovation provides the foundation for business . optimising Big Data analytics the seamless interconnecting of multiple. clouds and extended services for distributed applications that support. mobile devices and sensors , We hope this book offers some perspective on the opportunities made real. by such innovation both as a Big Data primer and for ongoing guidance. as your organisation embarks on that extended and hopefully fruitful . journey Please let us know what you think and how your Big Data. adventure progresses ,Cameron McNaught, Senior Vice President and Head of Strategic Solutions.
International Business,Fujitsu, 5, 1,What,is,Big,Data . 1 What is Big Data , In 2010 the term Big Data was virtually. unknown but by mid 2011 it was being, widely touted as the latest trend with all. the usual hype Like cloud computing , before it the term has today been adopted. by everyone from product vendors to, large scale outsourcing and cloud service.
providers keen to promote their offerings , But what really is Big Data . In short Big Data is about quickly deriving business value from a range of. new and emerging data sources including social media data location data. generated by smartphones and other roaming devices public information. available online and data from sensors embedded in cars buildings and. other objects and much more besides , Defining Big Data the 3V model. Many analysts use the 3V model to define Big Data The three Vs stand for Data speed. volume velocity and variety In a Big Data, world one of the. key factors is speed , Volume refers to the fact that Big Data involves analysing comparatively Traditional analytics. huge amounts of information typically starting at tens of terabytes focus on analysing. historical data , Velocity reflects the sheer speed at which this data is generated and Big data extends.
this concept to, changes For example the data associated with a particular hashtag on. include real time, Twitter often has a high velocity Tweets fly by in a blur In some instances analytics of in flight. they move so fast that the information they contain can t easily be stored transitory data . yet it still needs to be analysed , Variety describes the fact that Big Data can come from many different. sources in various formats and structures For example social media sites. Photograph iStockphoto, and networks of sensors generate a stream of ever changing data As well. as text this might include for example geographical information images . videos and audio , 7, Linked Data a new model for the database.
The growth of semi structured data see Data types right is driving the. adoption of new database models based on the idea of Linked Data These. reflect the way information is connected and represented on the Internet with. links cross referencing various pieces of associated information in a loose web . rather than requiring data to adhere to a rigid inflexible format where. everything sits in a particular predefined box Such an approach can provide the. flexibility of an unstructured data store along with the rigour of defined data. structures This can enhance the accuracy and quality of any query and. Data sources associated analyses , Big Data not only. extends the data, types but the, Value the fourth vital V. sources that the While the 3V model is a useful way of defining Big Data in this book we will also be. data is coming from concentrating on a fourth vital V value There is no point in organisations. to include real time implementing a Big Data solution unless they can see how it will give them. sensor and public increased business value That might not only mean using the data within their. data sources as well, as in house and own organisation value could also come from selling it or providing access to third. subscription sources parties This drive to maximise the value of Big Data is a key business imperative . There are other ways in which Big Data offers businesses new ways to generate. value For example whereas traditional business analytical systems had to. operate on historical data that might be weeks or months out of date a Big. Data solution can also analyse information being generated in real time or at. least close to real time This can deliver massive benefits for businesses as they. are able to respond more quickly to market trends challenges and changes . Furthermore Big Data solutions can add new value by analysing the sentiment. contained in the data rather than just looking at the raw information for example . they can understand how customers are feeling about a particular product This is. known as semantic analysis There are also growing developments in artificial. intelligence techniques that can be used to perform complex fuzzy searches and. unearth new previously impenetrable business insights from the data . In summary Big Data gives organisations the opportunity to exploit a. combination of existing data transient data and externally available data. sources in order to extract additional value through . l Improved business insights that lead to more informed decision making. l Treating data as an asset that can be traded and sold . It is therefore important that organisations keep sight of both the long term goal. of Big Data to integrate many data sources in order to unlock even more. 8, 1 What is Big Data , Data types, IT people classify data according to three basic types structured . unstructured and semi structured , Structured data refers to the type of data used by traditional database.
systems where records are split into well defined fields such as name . address etc which can be relatively easily searched categorised sorted. according to certain criteria etc , Unstructured data meanwhile has no obvious pre defined format for. example image data or Twitter updates , Semi structured data refers to a combination of the two types above . Some aspects of the data may be defined typically within the information. itself e g location data appended to social media updates but overall it. does not have the rigidity associated with structured data . The drive, potential value while ensuring their current technology is not a barrier to. to maximise,accuracy immediacy and flexibility the value. of Big Data, In many respects Big Data isn t new It is a logical extension of many existing is a key.
data analysis systems and concepts including data warehouses knowledge business. management KM business intelligence BI business insight and other areas. of information management , imperative ,Big Data the new cloud . The trouble with all new trends and buzz phrases is that they quickly become the. latest bandwagon for suppliers As noted at the start of this chapter all manner. of products and services are now being paraded under the Big Data banner . which can make the topic seem incredibly confusing hence this book This is. compounded when vendors whose products might only pertain to a small part of. the Big Data story grandly market them as Big Data solutions when in fact. they re just one element of a solution As a marketing term then be aware that. Big Data means about as much as the term cloud i e not a great deal . When is big really big , History tells us that yesterday s big is today s normal Some over 40s reading. this book will probably remember wondering how they were ever going to fill the. 1 kilobyte of memory on their Sinclair ZX81 Today we walk around with tens of. 9, gigabytes of memory on our smartphones Big Data simply refers to volumes of. data bigger than today s norm In 2012 a petabyte 1 million gigabytes seems. big to most people but tomorrow that volume will become normal and over. time just a medium to small amount of data , What s driving the need for Big Data solutions over traditional data warehouses. and BI systems therefore isn t some pre defined bigness of the data but a. combination of all three Vs From a business perspective this means IT. departments need to provide platforms that enable their business colleagues. to easily identify the data that will help them address their challenges . interrogate that data and visualise the answers effectively and quickly often. in near real time So forget size it s all about speed to decision Big Data in. a business sense should really be called quick answers . Near enough or mathematically perfect , When the concept of Big Data first emerged there was a lot of talk about.
IT departments relative accuracy It was said that over a large fluid set of data a Big Data. need to provide solution could give a good approximate answer but that organisations requiring. platforms that greater accuracy would need a traditional data warehouse or BI solution While. enable their that s still true to a degree many of today s Big Data solutions use the same. algorithms computational analysis methods as traditional BI systems . business meaning they re just as accurate Rather than fixating on the mathematical. colleagues to accuracy of the answers given by their systems organisations should instead. easily identify focus on the business relevance of those answers . the data that, will help them Big Data is so yesterday. Since Big Data has only been in common use since mid 2009 it might seem. address their, natural to assume that early adopters face the usual slew of teething problems . challenges However this is not the case That s not because the IT industry has become any. better at avoiding such problems Rather it s because although the term Big. Data may be relatively new the concept is certainly not . Consider an organisation like Reuters whose business model is based on. extracting relevant news from a mass of data and getting it to the right people. as quickly a possible it has been dealing with Big Data for over 100 years In. more recent years so have Twitter Facebook Google Amazon eBay and a raft. of other well known online names Today the bigger problem is that so much. data is thrown away ignored or locked up in silos where it adds minimal value . Being able to integrate available data from different sources in order to extract. approaches to Big Data adoption the issues that can hamper Big Data initiatives and the new skillsets that will be required by both IT specialists and management to deliver success At a fundamental level it also shows how to map business priorities onto an action plan for turning Big Data into increased revenues and lower costs

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