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BIG DATA TRENDS



11/15/2012
David Feinleib




THE BIG DATA GROUP   THEBIGDATAGROUP.COM
WHAT IS BIG DATA?




THEBIGDATAGROUP.COM
THEBIGDATAGROUP.COM
THEBIGDATAGROUP.COM
+




THEBIGDATAGROUP.COM
Outline



      1) Landscape - Number of Big Data
         Companies and Categories Is Growing
      2) Basic Stats - Consumer Scale Driving Big
         Data Transformation
      3) Transformation - Many Industries
      4) Top 8 Laws Of Big Data
      5) Big Data Whitespace

THEBIGDATAGROUP.COM                                 6
BASIC STATS - BIG DATA MARKET ROBUST,
 CONSUMER SCALE FUELING TECH ADOPTION




 METADATA GROUP
THEBIGDATAGROUP.COM
                                         7
Apps
            Vertical              Ad/Media                 Business      Analytics and
                                                         Intelligence    Visualization

     Operational Intelligence




                    Data As A Service


                                          Infrastructure
           Analytics             Operational            As A Service    Structured DB




                                          Technologies
                                                   8
Copyright © 2012 Dave Feinleib          dave@thebigdatagroup.com             bigdatalandscape.com
MARKET GROWTH




 METADATA GROUP
THEBIGDATAGROUP.COM
                      9
Big Data Overall Revenue $5.1B in ’11

                   Vendors With Big Data Revenues Over $100M

        IBM
       Intel
         HP
     Fujitsu
  Accenture
       CSC
        Dell
    Seagate
       EMC
   Teradata
   Amazon
        SAS
  Capgemini
     Hitachi
               0        250          500           750            1000
                                                         Source: Wikibon

THEBIGDATAGROUP.COM                                                        10
Big Data Pure-Play Revenue $468M in ’11




THEBIGDATAGROUP.COM                        11
Big Data Overall Revenue $53.4B By 2017




Billions




                                      Source: Wikibon

  THEBIGDATAGROUP.COM                                   12
DATA GROWTH




 METADATA GROUP
THEBIGDATAGROUP.COM
                      13
Facebook at 1B Users in Oct ’12

              1000



               750

  Users
In Millions
               500



               250


                                                                  Source: Benphoster.com
                0
                Dec 04   Apr 07   Jan 09   Jul 09   Feb 10   Jan 11    Sep 11      Oct 12


 THEBIGDATAGROUP.COM                                                                        14
Twitter at 400M Tweets Per Day in Jun ’12

          400



          300


 Tweets
Per Day In 200
 Millions


          100



                                                Source: Twitter blog and news reports
            0
            Jan 07   Jan 08   Oct 09   Sep 10      Jun 11        Oct 11          Jun 12

  THEBIGDATAGROUP.COM                                                                     15
94% Corporate Data Growth Y/Y



         Area                            Growth Rate

         Database systems                    97%

         Overall corporate data              94%

          Data of average organization       50%

                                               Source: Forrester




THEBIGDATAGROUP.COM                                                16
Big Data: By The Numbers




      •   Walmart handles 1M transactions per hour
      •   Google processes 24PB of data per day
      •   AT&T transfers 30PB of data per day
      •   90 trillion emails are sent per year
      •   World of Warcraft uses 1.3PB of storage


THEBIGDATAGROUP.COM
Worldwide Data Growth at 7.9EB / Yr in ‘15

            8000



            6000
 Exabytes




            4000



            2000



               0
                   2005   2010                    2015
                                 Source: IDC, EMC. 1EB = 1 Billion GB.

THEBIGDATAGROUP.COM
Bandwidth of Our Senses




THEBIGDATAGROUP.COM       Source: Hans Norretranders
Data Sensed Per Year


      0.04 EB                     7,910 EB



                      200,000X




                                 1EB = 1 Billion GB
THEBIGDATAGROUP.COM
THE BIG DATA CYCLE




 METADATA GROUP
THEBIGDATAGROUP.COM
                      21
As Efficiency Increases, So Does Consumption




                                 Source: Cloudyn


THEBIGDATAGROUP.COM                                22
The Big Data Cycle


 1 Consumer scale and
 1)
 speed requirements have
 introduced new
 technologies that have
 increased the efficiency of
                                            22) This increased efficiency
                                             is leading to adoption of Big
 using Big Data
                                             Data across a wide variety
                                             of industries

                        33) This results in the
                         generation and
                         consumption of more
                         data

THEBIGDATAGROUP.COM                                                     23
6 Insights From Facebook’s
Former Head Of Big Data
                       Analytics on 900M users
            25PB of compressed data - 125PB uncompressed




     1) “What data to store” => “What can we do with more data”
     2) Simplify data analytics for end users
     3) More users means analytics systems have to be more robust
     4) Social networking works for Big Data
     5) No single infrastructure can solve all Big Data problems
     6) Building software is hard; running a service is even harder



THEBIGDATAGROUP.COM                                                   24
BIG DATA TRANSFORMING BUSINESS




 METADATA GROUP
THEBIGDATAGROUP.COM
                                  25
Transformation of Retail

            THEN...             NOW...
                           Data driven pricing and
               Sales
                             recommendations




THEBIGDATAGROUP.COM                   Image: webdesignerdepot.com   26
Transformation of Online Marketing

                     THEN...                         NOW...
                                                 Marketing and Sales
                      Leads
                                                 Recommendations

Company      First    Last     Oppty   Created


  Acme       Fred     Langan   $250K   6/08/12
  BigCo      Tom      Jones    $100K   6/17/12
                                                     Campaign
 DealCo       Jan     Sedor    $50K    7/01/12
                                                  Recommendations
Stor Works   Liza     Grear    $750K   7/14/12

RF Group     Carl     Tomer    $47K    7/18/12




THEBIGDATAGROUP.COM                                                    27
Transformation of IT

         THEN...                     NOW...
           Log files       Operational intelligence




THEBIGDATAGROUP.COM    Image: blog.getsocialize.com/2012/location-showcase   28
Transformation of Customer Service

         THEN...                NOW...
           Unhappy
                              Customer insight
          customers




THEBIGDATAGROUP.COM                        Chart: Zendesk   29
Transformation of Billing

          THEN...              NOW...
        Manual coding       Intelligent coding




THEBIGDATAGROUP.COM                              30
Transformation Of Fraud Management

          THEN...            NOW...
        Credit databases     Social profiles




THEBIGDATAGROUP.COM                           31
Transformation Of Operations Management

            THEN...          NOW...
                             Automated
            Operations?
                             operations




THEBIGDATAGROUP.COM           Images: Jalopnik.com, SFPark   32
Transformation of Law Enforcement

            THEN...           NOW...
                             Crime hotspot
            Gut instinct
                               prediction




THEBIGDATAGROUP.COM            Images: Fanpop.com, paleo.sscnet.ucla.edu   33
Transformation of Medical Research

           THEN...              NOW...
           Keyword
                                Relevance
           searches




THEBIGDATAGROUP.COM                  Images: PubMed, Atigeo   34
Transformation of Fitness

            THEN...            NOW...
               Manual
                                 Goals +
              tracking
                               measurement



     Walk 45 minutes
     Smoothie
     Lift weights 20 minutes




THEBIGDATAGROUP.COM               Image: Store.Nike.com   35
TOP 8 LAWS OF BIG DATA




 METADATA GROUP
THEBIGDATAGROUP.COM
                          36
BIG DATA LAW #1



        The faster you analyze your data,
        the greater its predictive value.
        Companies are moving away from batch
        processing to real-time to gain competitive
        advantage.




THEBIGDATAGROUP.COM                                   37
BIG DATA LAW #2




        Maintain one copy of your data, not
        dozens. The more you copy and move your
        data, the less reliable it becomes (example:
        banking crisis).




THEBIGDATAGROUP.COM                                    38
BIG DATA LAW #3




        Use more diverse data, not just
        more data. More diverse data leads to
        greater insights. Combining multiple data
        sources can lead to the most interesting
        insights of all.



THEBIGDATAGROUP.COM                                 39
BIG DATA LAW #4




        Data has value far beyond what you
        originally anticipate. Don’t throw it
        away.




THEBIGDATAGROUP.COM                             40
BIG DATA LAW #5



        Plan for exponential growth. The
        number of photos, emails, and IMs while
        large, is limited by the number of people.
        Networked “sensor” data from mobile
        phones, GPS, and other devices is much
        larger.



THEBIGDATAGROUP.COM                                  41
BIG DATA LAW #6



        Solve a real pain point. Don’t think of
        Big Data as a stand-alone new, shiny,
        technology. Think about your core business
        problems and how to solve them by
        analyzing Big Data.




THEBIGDATAGROUP.COM                                  42
BIG DATA LAW #7




        Put data and humans together to
        get the most insight. More data alone
        isn’t sufficient. Look for ways to broaden the
        use of data across your organization.




THEBIGDATAGROUP.COM                                     43
BIG DATA LAW #8




        Big Data is transforming business
        the same way IT did. Those that fail to
        leverage the numerous internal and external
        data sources available will be leapfrogged by
        new entrants.




THEBIGDATAGROUP.COM                                     44
D2: DATA + DESIGN




 METADATA GROUP
THEBIGDATAGROUP.COM
                      45
Data Informs Design




             “The racing technology on the yachts competing for
              the America’s Cup will be the most advanced ever”
                      - The Wall Street Journal MarketWatch

THEBIGDATAGROUP.COM
Design Informs Data




               “Visualization is a form of knowledge compression”
                                 - David McCandless


THEBIGDATAGROUP.COM
Big Data Versus Romance




THEBIGDATAGROUP.COM
SUMMARY




 METADATA GROUP
THEBIGDATAGROUP.COM
                      49
Big Data White Space



      1) Visualization - cloud, mobile, collaboration
      2) Big Data Apps - verticals
      3) Trend analysis across multiple data sources
      4) Consumer behavior
      5) Public data for scoring
      6) New information / data service businesses

THEBIGDATAGROUP.COM                                     50
Summary


      1) Consumer company speed and scale requirements driving
         efficiencies in Big Data storage and analytics

      2) Quantity of machine data vastly increasing (examples:
         networked sensor data from mobile phones and GPS devices)

      3) Move away from batch to real-time

      4) Cloud services opening Big Data to all

      5) New and broader number of data sources being meshed
         together

      6) Big Data Apps (BDAs) means using Big Data is faster and
         easier

THEBIGDATAGROUP.COM                                                  51
Contact




        David Feinleib
        dave@thebigdatagroup.com




THEBIGDATAGROUP.COM                52

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Big Data Trends

  • 1. BIG DATA TRENDS 11/15/2012 David Feinleib THE BIG DATA GROUP THEBIGDATAGROUP.COM
  • 2. WHAT IS BIG DATA? THEBIGDATAGROUP.COM
  • 6. Outline 1) Landscape - Number of Big Data Companies and Categories Is Growing 2) Basic Stats - Consumer Scale Driving Big Data Transformation 3) Transformation - Many Industries 4) Top 8 Laws Of Big Data 5) Big Data Whitespace THEBIGDATAGROUP.COM 6
  • 7. BASIC STATS - BIG DATA MARKET ROBUST, CONSUMER SCALE FUELING TECH ADOPTION METADATA GROUP THEBIGDATAGROUP.COM 7
  • 8. Apps Vertical Ad/Media Business Analytics and Intelligence Visualization Operational Intelligence Data As A Service Infrastructure Analytics Operational As A Service Structured DB Technologies 8 Copyright © 2012 Dave Feinleib dave@thebigdatagroup.com bigdatalandscape.com
  • 9. MARKET GROWTH METADATA GROUP THEBIGDATAGROUP.COM 9
  • 10. Big Data Overall Revenue $5.1B in ’11 Vendors With Big Data Revenues Over $100M IBM Intel HP Fujitsu Accenture CSC Dell Seagate EMC Teradata Amazon SAS Capgemini Hitachi 0 250 500 750 1000 Source: Wikibon THEBIGDATAGROUP.COM 10
  • 11. Big Data Pure-Play Revenue $468M in ’11 THEBIGDATAGROUP.COM 11
  • 12. Big Data Overall Revenue $53.4B By 2017 Billions Source: Wikibon THEBIGDATAGROUP.COM 12
  • 13. DATA GROWTH METADATA GROUP THEBIGDATAGROUP.COM 13
  • 14. Facebook at 1B Users in Oct ’12 1000 750 Users In Millions 500 250 Source: Benphoster.com 0 Dec 04 Apr 07 Jan 09 Jul 09 Feb 10 Jan 11 Sep 11 Oct 12 THEBIGDATAGROUP.COM 14
  • 15. Twitter at 400M Tweets Per Day in Jun ’12 400 300 Tweets Per Day In 200 Millions 100 Source: Twitter blog and news reports 0 Jan 07 Jan 08 Oct 09 Sep 10 Jun 11 Oct 11 Jun 12 THEBIGDATAGROUP.COM 15
  • 16. 94% Corporate Data Growth Y/Y Area Growth Rate Database systems 97% Overall corporate data 94% Data of average organization 50% Source: Forrester THEBIGDATAGROUP.COM 16
  • 17. Big Data: By The Numbers • Walmart handles 1M transactions per hour • Google processes 24PB of data per day • AT&T transfers 30PB of data per day • 90 trillion emails are sent per year • World of Warcraft uses 1.3PB of storage THEBIGDATAGROUP.COM
  • 18. Worldwide Data Growth at 7.9EB / Yr in ‘15 8000 6000 Exabytes 4000 2000 0 2005 2010 2015 Source: IDC, EMC. 1EB = 1 Billion GB. THEBIGDATAGROUP.COM
  • 19. Bandwidth of Our Senses THEBIGDATAGROUP.COM Source: Hans Norretranders
  • 20. Data Sensed Per Year 0.04 EB 7,910 EB 200,000X 1EB = 1 Billion GB THEBIGDATAGROUP.COM
  • 21. THE BIG DATA CYCLE METADATA GROUP THEBIGDATAGROUP.COM 21
  • 22. As Efficiency Increases, So Does Consumption Source: Cloudyn THEBIGDATAGROUP.COM 22
  • 23. The Big Data Cycle 1 Consumer scale and 1) speed requirements have introduced new technologies that have increased the efficiency of 22) This increased efficiency is leading to adoption of Big using Big Data Data across a wide variety of industries 33) This results in the generation and consumption of more data THEBIGDATAGROUP.COM 23
  • 24. 6 Insights From Facebook’s Former Head Of Big Data Analytics on 900M users 25PB of compressed data - 125PB uncompressed 1) “What data to store” => “What can we do with more data” 2) Simplify data analytics for end users 3) More users means analytics systems have to be more robust 4) Social networking works for Big Data 5) No single infrastructure can solve all Big Data problems 6) Building software is hard; running a service is even harder THEBIGDATAGROUP.COM 24
  • 25. BIG DATA TRANSFORMING BUSINESS METADATA GROUP THEBIGDATAGROUP.COM 25
  • 26. Transformation of Retail THEN... NOW... Data driven pricing and Sales recommendations THEBIGDATAGROUP.COM Image: webdesignerdepot.com 26
  • 27. Transformation of Online Marketing THEN... NOW... Marketing and Sales Leads Recommendations Company First Last Oppty Created Acme Fred Langan $250K 6/08/12 BigCo Tom Jones $100K 6/17/12 Campaign DealCo Jan Sedor $50K 7/01/12 Recommendations Stor Works Liza Grear $750K 7/14/12 RF Group Carl Tomer $47K 7/18/12 THEBIGDATAGROUP.COM 27
  • 28. Transformation of IT THEN... NOW... Log files Operational intelligence THEBIGDATAGROUP.COM Image: blog.getsocialize.com/2012/location-showcase 28
  • 29. Transformation of Customer Service THEN... NOW... Unhappy Customer insight customers THEBIGDATAGROUP.COM Chart: Zendesk 29
  • 30. Transformation of Billing THEN... NOW... Manual coding Intelligent coding THEBIGDATAGROUP.COM 30
  • 31. Transformation Of Fraud Management THEN... NOW... Credit databases Social profiles THEBIGDATAGROUP.COM 31
  • 32. Transformation Of Operations Management THEN... NOW... Automated Operations? operations THEBIGDATAGROUP.COM Images: Jalopnik.com, SFPark 32
  • 33. Transformation of Law Enforcement THEN... NOW... Crime hotspot Gut instinct prediction THEBIGDATAGROUP.COM Images: Fanpop.com, paleo.sscnet.ucla.edu 33
  • 34. Transformation of Medical Research THEN... NOW... Keyword Relevance searches THEBIGDATAGROUP.COM Images: PubMed, Atigeo 34
  • 35. Transformation of Fitness THEN... NOW... Manual Goals + tracking measurement Walk 45 minutes Smoothie Lift weights 20 minutes THEBIGDATAGROUP.COM Image: Store.Nike.com 35
  • 36. TOP 8 LAWS OF BIG DATA METADATA GROUP THEBIGDATAGROUP.COM 36
  • 37. BIG DATA LAW #1 The faster you analyze your data, the greater its predictive value. Companies are moving away from batch processing to real-time to gain competitive advantage. THEBIGDATAGROUP.COM 37
  • 38. BIG DATA LAW #2 Maintain one copy of your data, not dozens. The more you copy and move your data, the less reliable it becomes (example: banking crisis). THEBIGDATAGROUP.COM 38
  • 39. BIG DATA LAW #3 Use more diverse data, not just more data. More diverse data leads to greater insights. Combining multiple data sources can lead to the most interesting insights of all. THEBIGDATAGROUP.COM 39
  • 40. BIG DATA LAW #4 Data has value far beyond what you originally anticipate. Don’t throw it away. THEBIGDATAGROUP.COM 40
  • 41. BIG DATA LAW #5 Plan for exponential growth. The number of photos, emails, and IMs while large, is limited by the number of people. Networked “sensor” data from mobile phones, GPS, and other devices is much larger. THEBIGDATAGROUP.COM 41
  • 42. BIG DATA LAW #6 Solve a real pain point. Don’t think of Big Data as a stand-alone new, shiny, technology. Think about your core business problems and how to solve them by analyzing Big Data. THEBIGDATAGROUP.COM 42
  • 43. BIG DATA LAW #7 Put data and humans together to get the most insight. More data alone isn’t sufficient. Look for ways to broaden the use of data across your organization. THEBIGDATAGROUP.COM 43
  • 44. BIG DATA LAW #8 Big Data is transforming business the same way IT did. Those that fail to leverage the numerous internal and external data sources available will be leapfrogged by new entrants. THEBIGDATAGROUP.COM 44
  • 45. D2: DATA + DESIGN METADATA GROUP THEBIGDATAGROUP.COM 45
  • 46. Data Informs Design “The racing technology on the yachts competing for the America’s Cup will be the most advanced ever” - The Wall Street Journal MarketWatch THEBIGDATAGROUP.COM
  • 47. Design Informs Data “Visualization is a form of knowledge compression” - David McCandless THEBIGDATAGROUP.COM
  • 48. Big Data Versus Romance THEBIGDATAGROUP.COM
  • 50. Big Data White Space 1) Visualization - cloud, mobile, collaboration 2) Big Data Apps - verticals 3) Trend analysis across multiple data sources 4) Consumer behavior 5) Public data for scoring 6) New information / data service businesses THEBIGDATAGROUP.COM 50
  • 51. Summary 1) Consumer company speed and scale requirements driving efficiencies in Big Data storage and analytics 2) Quantity of machine data vastly increasing (examples: networked sensor data from mobile phones and GPS devices) 3) Move away from batch to real-time 4) Cloud services opening Big Data to all 5) New and broader number of data sources being meshed together 6) Big Data Apps (BDAs) means using Big Data is faster and easier THEBIGDATAGROUP.COM 51
  • 52. Contact David Feinleib dave@thebigdatagroup.com THEBIGDATAGROUP.COM 52

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  4. The amount of detail is so impressive you might think this requires an elaborate and expensive set of monitoring gear. \n
  5. But unbelievably this can all be captured using a low cost off the shelf device combined with the online Garmin connect software. This truly epitomizes Big Data.\n
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