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What kinds of data go into Big Data?
Dan Wood, Solution Manager, HP Big Data
Mike Shaw, Director, HP Software Marketing
#mike_j_shaw
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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?
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Big data can give us the power of the 360-degree view… …combining structured and unstructured data
Structured data : 10%
Unstructured data : 90%
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Three types data can feed into big data
Machine to machine data
2 Human interaction data
3 Transaction data
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The three types of big data 1 - Transactions
Machine to machine data
2 Human interaction data
3 Transaction data
1
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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.
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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
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The three types of big data 2 – Machine to machine 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 computer power will soon be everywhere
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…much of it connected. In fact...
Mobile traffic increases 33X
A 33 times increase in mobile data traffic between 2010 and 2020.
2010 3.8 exabytes
2020 127 exabytes
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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%
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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
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The three types of big data 3 – Human interaction data
Machine to machine data
2 Human interaction data
3 Transaction data
1
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Meaning from human interaction comes from many sources
Social media
Images
Video
Audio
Documents
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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
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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
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Compliance departments can analyze company emails looking for non-compliant behavior…
…and for internal security breaches (e.g., sale of company assets to criminals).
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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
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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
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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
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Are you ready to support the business’s big data needs?
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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
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Are you getting insight from human interaction data?
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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%
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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
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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.