thinks…© 2012 – All rights reserved Fluxx Ltd.
“Ask 10 technology vendors to come and talk to you about big data andyou will get 15 different definitions.”              ...
“If you ask 10 experts what Big Data    means, you’ll get 15 different              answers”            TechRepublic      ...
What kind of “experts” are they?                                    thinks…           © 2012 – All rights reserved Fluxx L...
Conclusion:10 People = 15 Opinions          Eh?                             thinks…    © 2012 – All rights reserved Fluxx ...
What is ‘Big Data’ anyway?                                 thinks…        © 2012 – All rights reserved Fluxx Ltd.
What is ‘Big Data’                                     anyway?                         thinks…© 2012 – All rights reserved...
BIG The emphasis is usually on how complex orhard it will be to extract value from the largest                   of datase...
DATAThey imply there is stuff we need to know                in there.             But what is it?                        ...
“There are things we know we don’t know”              Donald Rumsfeld                                         thinks…     ...
Our definitionThe Big Data movement is the assumption that thereis useful insight to be had from datasets thathistorically...
A glimpse into my past                                thinks…       © 2012 – All rights reserved Fluxx Ltd.
Time to process   60   50   40   30   20   10    0        0         10000   20000                 30000                   ...
Time to process   60   50   40   30   20   10                                       10 years later, with Moore’s Law appli...
Time to process100  0      0          20000       40000         60000                         KB of data                  ...
2 years      Time to process100  0      0             20000   40000        60000                                          ...
The questions tonight are…1. Is it as hard as they make out?2. What kind of insight could be retrieved   from data?   Tell...
David                 Mark                                     SuranjanEllis, Station 10    Bjornsgaard, Fluxx            ...
Who’s Afraid of Big Bad Data?                      Or How to Stop Data Keeping You Up At Night0, 1, 1, 2, 3,   5,     8,  ...
Who are Station10?        Multiplatform & multichannel data, insight and optimisation experts0, 1, 1, 2, 3,   5,   8,   1...
The future is data, social & multiplatform                                                                 How prepared/un...
To understand data, we need to love maths!0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Who’s Afraid of Big Bad Maths?       Companies are not hiring those people whose       skills are on the fringes. They may...
Maths never scared this lot!0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
But we are good at spotting patterns0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
But we are good at spotting patterns            14            12            10             8                              ...
How to stop Big Data                      keeping you awake at night0, 1, 1, 2, 3,   5,    8,   13,   21,   34,   55,
“Call her Elsie!”0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Visualise the data!0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Visualise the data!0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Not all the data will necessarily be useful or accurate0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Understand how the consumer can be “irrational”                      SUBSCRIPTIONS                                        ...
It’s 1969 again, baby!0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Create an insight investigations team0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Data is power                           "We are looking for Predictive Modeling/Data Mining Scientists                    ...
The value of analysing big data0, 1, 1, 2, 3,   5,   8,   13,   21,   34,   55,
Summary        The maths behind big data should not be scary           Especially if you start to colour some of it in! ...
THANK YOU!                      david.ellis@station10.co.uk0, 1, 1, 2, 3,   5,     8,      13,         21,     34,   55,
flux[x]      BIG DATA, SMALL STRATEGY      Strategy by experimentation[x] fluxx.uk.com/consults           © 2012 – All rig...
Hello                                            flux[x]       /   Mark Bjornsgaard       /   Director Fluxx Adventures   ...
The next 30 mins…                                                    flux[x]       / Part 1 – A brilliant theory (10mins) ...
flux[x]       WHAT WE MEAN BY BIG DATA?[x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
flux[x]         Big data[x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
What is the data in big data?                                                               flux[x]                       ...
How does data become big?                                      flux[x]                                  Volume            ...
A definition…                                                               flux[x]   “Data that’s an order of   “Data tha...
Like its 1996 all over again…                 flux[x][x] fluxx.uk.com/consults           © 2012 – All rights reserved Flux...
flux[x]       HOW DOES IT REALLY WORK?[x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
How does it work?                                                                flux[x]                      Big data is…...
How does it work?                                    flux[x]                            “big data”                        ...
How does it work?                                                                             flux[x]                     ...
flux[x]      IN THE REAL WORLD[x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
In…retail                                           flux[x]    Then – have a sale      Now – target individuals[x] fluxx.u...
In…online marketing                                   flux[x]                            Now – triangulate multiple    The...
In…IT                                                flux[x]    Then – data locked in   Now – rich, real time    unusable ...
In…risk management                                    flux[x]                              Now – telematics and    Then – ...
In…law enforcement                                 flux[x]                            Now – crime hotspot    Then – gut in...
In…medical research                                  flux[x]                              Now – semantic and NLP    Then –...
In…sports                                               flux[x]    Then – subjective “truth”   Now – objective insight[x] ...
flux[x]       PART 2       IN THE REAL WORLD[x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
90% of colleagues don’t really care                 flux[x][x] fluxx.uk.com/consults                 © 2012 – All rights r...
A Vanguard doesn’t really exist                 flux[x][x] fluxx.uk.com/consults             © 2012 – All rights reserved ...
Use cases are still limited                                                           flux[x]                             ...
Hires are scarce…                     flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
R and Hadoop aren’t for all techies…                 flux[x][x] fluxx.uk.com/consults                  © 2012 – All rights...
flux[x]    Big data only shows us what’s not obvious…[x] fluxx.uk.com/consults               © 2012 – All rights reserved ...
So…using big data actually means….                                 flux[x]       /   Colleagues who are biologically pre-p...
flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
flux[x]      PART 3      STRATEGY BY EXPERIMENTATION[x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
Strategy by experimentation                 flux[x][x] fluxx.uk.com/consults         © 2012 – All rights reserved Fluxx Ltd.
1. Set aside some time (and budget)                 flux[x][x] fluxx.uk.com/consults                 © 2012 – All rights r...
2. Find a partner you trust                 flux[x][x] fluxx.uk.com/consults         © 2012 – All rights reserved Fluxx Ltd.
3. Get everyone involved                 flux[x][x] fluxx.uk.com/consults      © 2012 – All rights reserved Fluxx Ltd.
4. Identify a business issue you have…                                                   flux[x]                          ...
5. Identify data sets which might hold                                                       flux[x]    clues             ...
6. Play detective                                     flux[x]           Patterns         Relationships          Correlatio...
7. Rinse and repeat                   flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
8. Re-humanise the story…                 flux[x][x] fluxx.uk.com/consults       © 2012 – All rights reserved Fluxx Ltd.
9. Shout about it                     flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
10. Enjoy the journey                 flux[x][x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
To summarise                                             flux[x]       / Define big data for yourself – see how it could  ...
flux[x]      THANK YOU![x] fluxx.uk.com/consults   © 2012 – All rights reserved Fluxx Ltd.
How not to eatan elephantSuranjan Som | Head of BI Practice
“As consumertechnology innovationand a culture of socialdecision-makingchanges the way thatour customers makedecisions abo...
CustomerCentric
BigData
Customer intelligence hashistorically relied onassumptions based ontransactional behavioranalysis
“Big Data presents uswith some veryexciting short andmedium term winsaround customerinsight. But the moststrategic opportu...
Business Transformation & EnablementOrganisational Governance                                                             ...
Outsource Risk                   Specialist Business UsersBlended Resource                        Data ScientistsOpportuni...
Data Production             Data Storage & Management               Data Exploitation1. Data Acquisition         2. Data T...
Validity
Analytics                     Multi-platform Delivery          Document Management                   Business Abstraction ...
“Big data” is based on a single fear:   There might be something powerful        and useful in all that data!             ...
“There are things we know we don’t know”              Donald Rumsfeld                                         thinks…     ...
So the holding position has beenhang on to it, otherwise we’ll regret it later                                          th...
thinks…© 2012 – All rights reserved Fluxx Ltd.
thinks…© 2012 – All rights reserved Fluxx Ltd.
So the holding position isA total boon for the storage industry!        But equally,… it’s hard to argue with!            ...
But our (real) experts have told us:  1. It doesn’t have to be big to be useful  2. Big doesn’t always mean complex  3. Th...
In other wordsSize isn’t important, it’s what  you do with it that counts                                           thinks...
In other wordsSize isn’t important, it’s what  you do with it that counts                                           thinks...
In other wordsSize isn’t important, it’s what  you do with it that counts                                           thinks...
In other words                                          Size isn’t                                    important, it’s what...
In other words                            Size important isn’t .                           Matters only what you do       ...
thinks…© 2012 – All rights reserved Fluxx Ltd.
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
Fluxx-Don't be a (big) data hater event-181012-main presentation
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The main presentation from our "Don't be a (big) data hater" event held at Fluxx Studios on 18th October 2012.

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  • <graphic of a processing time versus computing power graph that shows how long it used to take to run a report across a series of retail stores and how this has come down over time><Then another that shows what happens to the time taken when the amount of data goes up by 100-fold>
  • <graphic of a processing time versus computing power graph that shows how long it used to take to run a report across a series of retail stores and how this has come down over time><Then another that shows what happens to the time taken when the amount of data goes up by 100-fold>
  • <graphic of a processing time versus computing power graph that shows how long it used to take to run a report across a series of retail stores and how this has come down over time><Then another that shows what happens to the time taken when the amount of data goes up by 100-fold>
  • <graphic of a processing time versus computing power graph that shows how long it used to take to run a report across a series of retail stores and how this has come down over time><Then another that shows what happens to the time taken when the amount of data goes up by 100-fold>
  • The secret to analysing and understanding large data sets is to look at them in a different way.The most valuable analytical tools for large data sets are those that can show the data in a way we can understand them more easily.
  • 574
  • Just because data volumes are large, this doesn’t mean that all data captured is accurateFacebook now has “1 billion” active visitorsBut it also can automatically add “likes” without that user clicking the like button (or even seeing the page)This raises questions about the accuracy of the data, but also whether all metrics, like visitors, are correct
  • With the rise of available data, new fields such as behavioural economics are emerging that look to understand what forces can influence customers’ behaviour and decision-making.This means that data can be telling you the right things, even if it doesn’t seem to make sense at first sight
  • Traditional MI “cube” databases are very good at regular reporting But they are less good at running detailed queries against massive data sets for initial researchLinear databases are much more efficient for initial researchConsider using two tools to analyse dataOne for regular reporting, and a “rapid response unit”Linear databases can give you different answers to what appears to be the same questionBut they can also answer questions that most MI tools cannotThis means it is really important to understand both the tools you have and the data you hold to ensure that you are answering them correctly
  • Give them the tools to find the insights that you are looking for.Be prepared to use different tools to analyse large data sets
  • If the ultimate concept of celebrity, or at least popularity, is politics, then Obama’s advert for data analysts shows how valuable data and its correct understanding can be.
  • A global telco’s call centre in the US wanted to analyse the multichannel data that influenced usage of their call centre.This included web traffic that preceded and followed a call to the call centre, and what insights could be gained and recommendations to drive improvements.Initial analysis to identify 10 optimisation recommendations took less than one week.By reducing call centre traffic by 2%, the telco established it would save $600m per annum.
  • break it down, Demystify it
  • Marketing and intelligence point of view
  • New products, new channels to market, new customers
  • Getting to that insight is exponwntiallyahrder than everyone says it is, getting that insight used and understood is even harderWhy?
  • Fluxx-Don't be a (big) data hater event-181012-main presentation

    1. 1. thinks…© 2012 – All rights reserved Fluxx Ltd.
    2. 2. “Ask 10 technology vendors to come and talk to you about big data andyou will get 15 different definitions.” ZD.net thinks… © 2012 – All rights reserved Fluxx Ltd.
    3. 3. “If you ask 10 experts what Big Data means, you’ll get 15 different answers” TechRepublic thinks… © 2012 – All rights reserved Fluxx Ltd.
    4. 4. What kind of “experts” are they? thinks… © 2012 – All rights reserved Fluxx Ltd.
    5. 5. Conclusion:10 People = 15 Opinions Eh? thinks… © 2012 – All rights reserved Fluxx Ltd.
    6. 6. What is ‘Big Data’ anyway? thinks… © 2012 – All rights reserved Fluxx Ltd.
    7. 7. What is ‘Big Data’ anyway? thinks…© 2012 – All rights reserved Fluxx Ltd.
    8. 8. BIG The emphasis is usually on how complex orhard it will be to extract value from the largest of datasets. thinks… © 2012 – All rights reserved Fluxx Ltd.
    9. 9. DATAThey imply there is stuff we need to know in there. But what is it? thinks… © 2012 – All rights reserved Fluxx Ltd.
    10. 10. “There are things we know we don’t know” Donald Rumsfeld thinks… © 2012 – All rights reserved Fluxx Ltd.
    11. 11. Our definitionThe Big Data movement is the assumption that thereis useful insight to be had from datasets thathistorically were too large to meaningfully analyse. For example: Detailed click by click visitor data from internet sites Information about individuals’ social network interactions and relationships thinks… © 2012 – All rights reserved Fluxx Ltd.
    12. 12. A glimpse into my past thinks… © 2012 – All rights reserved Fluxx Ltd.
    13. 13. Time to process 60 50 40 30 20 10 0 0 10000 20000 30000 40000 50000 60000 KB of data thinks… © 2012 – All rights reserved Fluxx Ltd.
    14. 14. Time to process 60 50 40 30 20 10 10 years later, with Moore’s Law applied 0 0 10000 20000 30000 40000 50000 60000 KB of data thinks… © 2012 – All rights reserved Fluxx Ltd.
    15. 15. Time to process100 0 0 20000 40000 60000 KB of data thinks… © 2012 – All rights reserved Fluxx Ltd.
    16. 16. 2 years Time to process100 0 0 20000 40000 60000 10 terabytes KB of data thinks… © 2012 – All rights reserved Fluxx Ltd.
    17. 17. The questions tonight are…1. Is it as hard as they make out?2. What kind of insight could be retrieved from data? Tell us something we don’t know…. thinks… © 2012 – All rights reserved Fluxx Ltd.
    18. 18. David Mark SuranjanEllis, Station 10 Bjornsgaard, Fluxx Som, IM Group [Adventures] Time for some proper content thinks… © 2012 – All rights reserved Fluxx Ltd.
    19. 19. Who’s Afraid of Big Bad Data? Or How to Stop Data Keeping You Up At Night0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    20. 20. Who are Station10?  Multiplatform & multichannel data, insight and optimisation experts0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    21. 21. The future is data, social & multiplatform How prepared/unprepared is your organisation for the following upcoming trends over the next 5 years?  4 out of 5 CMOs anticipate a high/very high level of data complexity over the next 5 years, but only half felt ready to handle it.0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, Source: Econsultancy, Oct 2011
    22. 22. To understand data, we need to love maths!0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    23. 23. Who’s Afraid of Big Bad Maths? Companies are not hiring those people whose skills are on the fringes. They may well be an honourable person but…they’ll be told, You just don’t have the mathematical skills that are nowadays required.’” Eric Schmidt, Chairman, Google0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    24. 24. Maths never scared this lot!0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    25. 25. But we are good at spotting patterns0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    26. 26. But we are good at spotting patterns 14 12 10 8 Snail 6 Fibonnacci 4 2 0 1 2 3 4 5 6 70, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    27. 27. How to stop Big Data keeping you awake at night0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    28. 28. “Call her Elsie!”0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    29. 29. Visualise the data!0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    30. 30. Visualise the data!0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    31. 31. Not all the data will necessarily be useful or accurate0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    32. 32. Understand how the consumer can be “irrational” SUBSCRIPTIONS SUBSCRIPTIONS Welcome to Welcome to The Economist Subscription Centre The Economist Subscription Centre Pick the type of subscription you want to buy or renew. Pick the type of subscription you want to buy or renew. Economist.com subscription – US $59.00 Economist.com subscription – US $59.00 One-year subscription to Economist.com. 16 One-year subscription to Economist.com. 68 Includes online access to all articles from The Economist since Includes online access to all articles from The Economist since 1997. 1997. Print subscription – US $125.00 0 Print & web subscription – US $125.00 32 One-year subscription to the print edition of The Economist. One-year subscription to the print edition of The Economist and online access to all articles from The Economist since 1997. Print & web subscription – US $125.00 84 One-year subscription to the print edition of The Economist and online access to all articles from The Economist since 1997.0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    33. 33. It’s 1969 again, baby!0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    34. 34. Create an insight investigations team0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    35. 35. Data is power "We are looking for Predictive Modeling/Data Mining Scientists and Analysts, at both the senior and junior level, to join our department through November 2012 at our Chicago Headquarters,” read the ad. "We are a multi-disciplinary team of statisticians, predictive modelers, data mining experts, mathematicians, software developers, general analysts and organizers -all striving for a single goal: re-electing President Obama."0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, Source: Econsultancy, Feb 2012
    36. 36. The value of analysing big data0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    37. 37. Summary  The maths behind big data should not be scary  Especially if you start to colour some of it in!  Learn what is inaccurate or unusual in the data  Make sure you have the right team and right tools for the job  Look to understand your consumer  Enjoy!0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    38. 38. THANK YOU! david.ellis@station10.co.uk0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55,
    39. 39. flux[x] BIG DATA, SMALL STRATEGY Strategy by experimentation[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    40. 40. Hello flux[x] / Mark Bjornsgaard / Director Fluxx Adventures / Technology incubator / Invests in our own ideas[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    41. 41. The next 30 mins… flux[x] / Part 1 – A brilliant theory (10mins)  What we mean by Big Data?  How does it really work?  In the real world / Part 2 – The real story (10mins)  The 7 things they don’t tell you about using big data / Part 3 – Strategy by experimentation (10mins)[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    42. 42. flux[x] WHAT WE MEAN BY BIG DATA?[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    43. 43. flux[x] Big data[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    44. 44. What is the data in big data? flux[x] Sales data (epos and online) Web Sensor data analytics Big Documents Advertising and email Data analytics Sets Unstructured CRM social data databases Machine data – website logs[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    45. 45. How does data become big? flux[x] Volume Velocity Variety[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    46. 46. A definition… flux[x] “Data that’s an order of “Data that exceeds the “A set of technology magnitude bigger than we processing capacity of advances that have made are accustomed to” conventional database capturing and analysing systems. The data is too data at high scale and big, moves too fast, or speed vastly more doesn’t fit the structures of efficient” our database architectures”[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    47. 47. Like its 1996 all over again… flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    48. 48. flux[x] HOW DOES IT REALLY WORK?[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    49. 49. How does it work? flux[x] Big data is…..“ A set of technology advances that have made capturing and analysing data at high scale and speed vastly more efficient” Data scientists R Hadoop[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    50. 50. How does it work? flux[x] “big data” Your data[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    51. 51. How does it work? flux[x] “big data” 6 5 4 3 2 1 0 Your data Category 1 Category 2 Category 3 Category 4[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    52. 52. flux[x] IN THE REAL WORLD[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    53. 53. In…retail flux[x] Then – have a sale Now – target individuals[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    54. 54. In…online marketing flux[x] Now – triangulate multiple Then - pipeline data sets to identify targets[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    55. 55. In…IT flux[x] Then – data locked in Now – rich, real time unusable formats analytics[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    56. 56. In…risk management flux[x] Now – telematics and Then – paper validation unstructured data[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    57. 57. In…law enforcement flux[x] Now – crime hotspot Then – gut instinct identification[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    58. 58. In…medical research flux[x] Now – semantic and NLP Then – keyword searches “understanding”[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    59. 59. In…sports flux[x] Then – subjective “truth” Now – objective insight[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    60. 60. flux[x] PART 2 IN THE REAL WORLD[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    61. 61. flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    62. 62. flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    63. 63. 90% of colleagues don’t really care flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    64. 64. A Vanguard doesn’t really exist flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    65. 65. Use cases are still limited flux[x] Digital marketing x Data retention, d ata archiving Big Data exploration and discovery x Data x Machine- Fraud generated detection data and xanalytics Social network and relationship analysis x prevention[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    66. 66. Hires are scarce… flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    67. 67. R and Hadoop aren’t for all techies… flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    68. 68. flux[x] Big data only shows us what’s not obvious…[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    69. 69. So…using big data actually means…. flux[x] / Colleagues who are biologically pre-programmed not to care / No best practice to rely on / Very specific use cases within business / Hiring aching expensive people / To use software anyone with an IQ <150 shouldn’t go near / All in the cause of…..looking for non conclusive, obscure patterns, which may or may not lead to any business value[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    70. 70. flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    71. 71. flux[x] PART 3 STRATEGY BY EXPERIMENTATION[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    72. 72. Strategy by experimentation flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    73. 73. 1. Set aside some time (and budget) flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    74. 74. 2. Find a partner you trust flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    75. 75. 3. Get everyone involved flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    76. 76. 4. Identify a business issue you have… flux[x] What kind of Why is the ROI people make the on my CPC largest account purchases? declining? There’s always a How can I drive sales spike on sales of Thursday recommendation evenings – why? s in the check out process?[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    77. 77. 5. Identify data sets which might hold flux[x] clues Adwords data Social data Web analytics data There’s always a sales Store footfall spike on Thursday evenings – why? Brand tracking Transactional data Logistics files[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    78. 78. 6. Play detective flux[x] Patterns Relationships Correlations[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    79. 79. 7. Rinse and repeat flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    80. 80. 8. Re-humanise the story… flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    81. 81. 9. Shout about it flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    82. 82. 10. Enjoy the journey flux[x][x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    83. 83. To summarise flux[x] / Define big data for yourself – see how it could apply to you / Accept the challenges / Start small, grow and publicise success[x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    84. 84. flux[x] THANK YOU![x] fluxx.uk.com/consults © 2012 – All rights reserved Fluxx Ltd.
    85. 85. How not to eatan elephantSuranjan Som | Head of BI Practice
    86. 86. “As consumertechnology innovationand a culture of socialdecision-makingchanges the way thatour customers makedecisions about theirpurchases, it isbecomingincreasingly difficultto differentiate ourproducts and servicesfrom those of ourcompetition”
    87. 87. CustomerCentric
    88. 88. BigData
    89. 89. Customer intelligence hashistorically relied onassumptions based ontransactional behavioranalysis
    90. 90. “Big Data presents uswith some veryexciting short andmedium term winsaround customerinsight. But the moststrategic opportunityfor us is in theintegration of BigData to enrich theintelligence we holdaround our singleview of customer”
    91. 91. Business Transformation & EnablementOrganisational Governance Compliance & Regulatory Information Governance Information Delivery Solution Delivery Information Services Information Stores Information Integration Infrastructure
    92. 92. Outsource Risk Specialist Business UsersBlended Resource Data ScientistsOpportunity Data Services & Operations Technology Specialists
    93. 93. Data Production Data Storage & Management Data Exploitation1. Data Acquisition 2. Data Transformation 3. Data Enrichment 4. Data Dissemination 5. Data Disposal 6. Data Governance 7. Data Lifecycle Management
    94. 94. Validity
    95. 95. Analytics Multi-platform Delivery Document Management Business Abstraction Layer Big Data Relational Data Unstructured Data Structured Data Documents
    96. 96. “Big data” is based on a single fear: There might be something powerful and useful in all that data! thinks… © 2012 – All rights reserved Fluxx Ltd.
    97. 97. “There are things we know we don’t know” Donald Rumsfeld thinks… © 2012 – All rights reserved Fluxx Ltd.
    98. 98. So the holding position has beenhang on to it, otherwise we’ll regret it later thinks… © 2012 – All rights reserved Fluxx Ltd.
    99. 99. thinks…© 2012 – All rights reserved Fluxx Ltd.
    100. 100. thinks…© 2012 – All rights reserved Fluxx Ltd.
    101. 101. So the holding position isA total boon for the storage industry! But equally,… it’s hard to argue with! thinks… © 2012 – All rights reserved Fluxx Ltd.
    102. 102. But our (real) experts have told us: 1. It doesn’t have to be big to be useful 2. Big doesn’t always mean complex 3. The insight is worth it thinks… © 2012 – All rights reserved Fluxx Ltd.
    103. 103. In other wordsSize isn’t important, it’s what you do with it that counts thinks… © 2012 – All rights reserved Fluxx Ltd.
    104. 104. In other wordsSize isn’t important, it’s what you do with it that counts thinks… © 2012 – All rights reserved Fluxx Ltd.
    105. 105. In other wordsSize isn’t important, it’s what you do with it that counts thinks… © 2012 – All rights reserved Fluxx Ltd.
    106. 106. In other words Size isn’t important, it’s what you do with it that counts thinks…© 2012 – All rights reserved Fluxx Ltd.
    107. 107. In other words Size important isn’t . Matters only what you do with it. thinks…© 2012 – All rights reserved Fluxx Ltd.
    108. 108. thinks…© 2012 – All rights reserved Fluxx Ltd.

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