What kinds of data go into big data?
 

What kinds of data go into big data?

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What kinds of data go into big Data? And what kinds of insights can be revealed by combining the different kinds of data? Mike Shaw and Dan Wood of HP Software explore these questions.

What kinds of data go into big Data? And what kinds of insights can be revealed by combining the different kinds of data? Mike Shaw and Dan Wood of HP Software explore these questions.

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What kinds of data go into big data? What kinds of data go into big data? Presentation Transcript

  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.1 What kinds of data go into Big Data? Dan Wood, Solution Manager, HP Big Data Mike Shaw, Director, HP Software Marketing #mike_j_shaw
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.2 Much higher volumes Processed with more velocity With much more variety And a greater need to protect from vulnerabilities What is big data versus normal data?
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Bigdatacangiveusthepower ofthe360-degreeview… …combiningstructuredand unstructureddata Structured data : 10% Unstructured data : 90%
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Threetypesdatacanfeedinto bigdata Machine to machine data 2 Human interaction data 3 Transaction data 1
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. The three types of big data 1-Transactions Machine to machine data 2 Human interaction data 3 Transaction data 1
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.6 Big data can analyze transactions faster Retailer Guess is able to adjust shops’ layout in time for opening. Kokubu is a able to optimize distribution from its 200+ centers.
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.7 The HP.com team keeps transactionsfor 15 years. They look for ‘long-run affinities’ – buying patterns over long periods of time. …and over a longer time period
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. The three types of big data 2–Machine tomachine data Machine to machine data 2 Human interaction data 3 Transaction data 1
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Kitchen appliances Wearable monitors Medical robots Cars Tvs Automated factories Exercise machines Parking control Shopping trolley Security devices Cooking Road-side sensors Smart power Bikes Poaching sensors House control Shopping displays Smart phones Wearable devices Sensors Smart devices Tablets Smart phones The internet of things Everyday devices are infused with intelligence that is updated in real time. Embedded, connected computerpower willsoonbe everywhere
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. …muchofit connected. Infact... Mobile traffic increases 33X A 33 times increase in mobile data traffic between 2010 and 2020. 2010 3.8 exabytes 2020 127 exabytes
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.11 By 2020 there will be 6 billion mobile phones but 30 billion connected smart devices taking 42% of the mobile bandwidth. Machine generated data is estimated to reach 42% of mobile traffic by 2020 2020 42% 2013 33% 2005 11%
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.12 How we will our use of machine-to-machine data evolve? 2010 2015 McKinsey : Big Data – The next frontier for innovation, competition and productivity Automotive Utilities Travel / logistics Security Retail The internet of things • Medical equipment • Utility networks and meters • Car and truck fleets • Security sensors • Home automation • Touch-streams from games • Drones • Pollution sensors • Transport sensors
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. The three types of big data 3–Human interactiondata Machine to machine data 2 Human interaction data 3 Transaction data 1
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.14 Meaning from human interaction comes from many sources Social media Images Video Audio Email Documents
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.15 We can analyze the calls made to call centers— looking for products customers do and don't like, for opportunities to up-sell and cross-sell, and for those calls where the customer is about to "churn". Financial services companies use voice analysis to catch non-compliance behavior. Audio
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.16 During the London Olympics, British security services used HP technology to compare the photograph of every visitor to the games against a list of known terror suspects. We routinely perform number plate and car type recognition, scene recognition, facial recognition and perimeter enforcement at airports and military bases. Images Video
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.17 Compliance departments can analyze company emails looking for non-compliant behavior… …and for internal security breaches (e.g., sale of company assets to criminals). Email
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.18 Social media data can tell us all sort of things. It can tell us about our products, about our competitors, about the likelihood of customers "churning" from us and about cheating and fraud. Social media
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.19 Automatically extracting meaning from legal documentation allows us to do legal discovery more quickly and cheaply. Extracting meaning from case notes and then sharing this meaning between social care agencies might help to reduce interdepartmental failures of care. Documents
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Companies can use human information and big data…
  • To catch cheaters We use micro-transactions analysis to catch those who cheat at online gambling games. But cheats like to tell others about how clever they are on social media. Combining micro-transactions with social media allows us to find cheats faster than any one data type alone would.
  • To get closer to customers You can record every sale in every one of your retail stores and every transaction on your web site. This will tell you what items are trending and what items are being purchased together. You can use sentiment analysis to tell you about "cool stuff" that maybe you don't yet stock but should; and about competitors trending up quickly.
  • You can record and analyze transactions to look for fraud and non-compliance of traders. And analyze your company's emails and internal phone calls to get a “human interaction” view on non-compliance. To improve compliance within financial trading
  • HP Operations Analytics records metric, event and log information— and from this, allows support staff to fix complex problems. They could also analyze the “human” interactions between the support center and the app dev team, then correlate this with the structured information. To solve problems with complex systems
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Are you ready to support the business’s big data needs?
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.26 The survey says—probably not! Source : IDG survey for HP, 2014 : “Do you feel ready to handle different forms of structured big data?” 8% Online clickstreams 15% Machine data 23% Transaction data
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. Are you getting insight from human interaction data?
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.28 The survey says—probably not! Source : IDG survey for HP, 2014 51% To some extent 30% To little extent 2% Not applicable To no extent 13% To a great extent 5%
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.29 Find out more… Explore the whitepaper: See the big picture in Big Data …or fill out the info form on the next page Watch the SlideShare: Get closer to your customers with Big Data
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.30 Get the insight you need to take action: www.hp.com/HAVEn
  • © Copyright 2014 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.