Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Big Data Trends

104,810 views

Published on

A presentation on Big Data Trends. Covers market growth, industry transformation, the 3 I's of Big Data, and the 8 Laws of Big Data.

Published in: Technology, Business

Big Data Trends

  1. BIG DATA TRENDS11/15/2012David FeinleibTHE BIG DATA GROUP THEBIGDATAGROUP.COM
  2. WHAT IS BIG DATA?THEBIGDATAGROUP.COM
  3. THEBIGDATAGROUP.COM
  4. THEBIGDATAGROUP.COM
  5. +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 WhitespaceTHEBIGDATAGROUP.COM 6
  7. BASIC STATS - BIG DATA MARKET ROBUST, CONSUMER SCALE FUELING TECH ADOPTION METADATA GROUPTHEBIGDATAGROUP.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 8Copyright © 2012 Dave Feinleib dave@thebigdatagroup.com bigdatalandscape.com
  9. MARKET GROWTH METADATA GROUPTHEBIGDATAGROUP.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: WikibonTHEBIGDATAGROUP.COM 10
  11. Big Data Pure-Play Revenue $468M in ’11THEBIGDATAGROUP.COM 11
  12. Big Data Overall Revenue $53.4B By 2017Billions Source: Wikibon THEBIGDATAGROUP.COM 12
  13. DATA GROWTH METADATA GROUPTHEBIGDATAGROUP.COM 13
  14. Facebook at 1B Users in Oct ’12 1000 750 UsersIn 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 TweetsPer 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: ForresterTHEBIGDATAGROUP.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 storageTHEBIGDATAGROUP.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 SensesTHEBIGDATAGROUP.COM Source: Hans Norretranders
  20. Data Sensed Per Year 0.04 EB 7,910 EB 200,000X 1EB = 1 Billion GBTHEBIGDATAGROUP.COM
  21. THE BIG DATA CYCLE METADATA GROUPTHEBIGDATAGROUP.COM 21
  22. As Efficiency Increases, So Does Consumption Source: CloudynTHEBIGDATAGROUP.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 dataTHEBIGDATAGROUP.COM 23
  24. 6 Insights From Facebook’sFormer 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 harderTHEBIGDATAGROUP.COM 24
  25. BIG DATA TRANSFORMING BUSINESS METADATA GROUPTHEBIGDATAGROUP.COM 25
  26. Transformation of Retail THEN... NOW... Data driven pricing and Sales recommendationsTHEBIGDATAGROUP.COM Image: webdesignerdepot.com 26
  27. Transformation of Online Marketing THEN... NOW... Marketing and Sales Leads RecommendationsCompany 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 RecommendationsStor Works Liza Grear $750K 7/14/12RF Group Carl Tomer $47K 7/18/12THEBIGDATAGROUP.COM 27
  28. Transformation of IT THEN... NOW... Log files Operational intelligenceTHEBIGDATAGROUP.COM Image: blog.getsocialize.com/2012/location-showcase 28
  29. Transformation of Customer Service THEN... NOW... Unhappy Customer insight customersTHEBIGDATAGROUP.COM Chart: Zendesk 29
  30. Transformation of Billing THEN... NOW... Manual coding Intelligent codingTHEBIGDATAGROUP.COM 30
  31. Transformation Of Fraud Management THEN... NOW... Credit databases Social profilesTHEBIGDATAGROUP.COM 31
  32. Transformation Of Operations Management THEN... NOW... Automated Operations? operationsTHEBIGDATAGROUP.COM Images: Jalopnik.com, SFPark 32
  33. Transformation of Law Enforcement THEN... NOW... Crime hotspot Gut instinct predictionTHEBIGDATAGROUP.COM Images: Fanpop.com, paleo.sscnet.ucla.edu 33
  34. Transformation of Medical Research THEN... NOW... Keyword Relevance searchesTHEBIGDATAGROUP.COM Images: PubMed, Atigeo 34
  35. Transformation of Fitness THEN... NOW... Manual Goals + tracking measurement Walk 45 minutes Smoothie Lift weights 20 minutesTHEBIGDATAGROUP.COM Image: Store.Nike.com 35
  36. TOP 8 LAWS OF BIG DATA METADATA GROUPTHEBIGDATAGROUP.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 GROUPTHEBIGDATAGROUP.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 MarketWatchTHEBIGDATAGROUP.COM
  47. Design Informs Data “Visualization is a form of knowledge compression” - David McCandlessTHEBIGDATAGROUP.COM
  48. Big Data Versus RomanceTHEBIGDATAGROUP.COM
  49. SUMMARY METADATA GROUPTHEBIGDATAGROUP.COM 49
  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 businessesTHEBIGDATAGROUP.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 easierTHEBIGDATAGROUP.COM 51
  52. Contact David Feinleib dave@thebigdatagroup.comTHEBIGDATAGROUP.COM 52

×