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The Value of Big Data
From Data-Driven Enterp...
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Fraunhofer IAIS: Intelligent Analysis and Inf...
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Prof. Dr. Stefan Wrobel 3
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Fraunhofer Alliance Big Data
Joint competence...
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(Germany)
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www.
Open Data
Big Data Trends
C...
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Open Data
Big Data Trends
C...
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Big Data
A definition attempt
Big Data in gen...
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Big Data
The view of BITKOM, The German IT As...
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Sources/©: http://m.sybase.com/detail?id=1095...
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Innovation study Big Data
Desk research
(curr...
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Big Data Competitive Edge
Prof. Dr. Stefan Wr...
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Big Data Uptake Worldwide
U.S. Ahead, Europe ...
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Big Data ROI
Very positive ROIs across all re...
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Big Data Efforts Will Increase
Comparison of ...
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Use Of Big Data in Company Functions
From con...
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...
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Big Data Comprehensive Strategies Rare
Only f...
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Barriers to Big Data in Companies
Prof. Dr. S...
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Big Data – Challenges towards Data Value
Big ...
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Big Data – Challenges towards Data Value
Big ...
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Big Data and the Digital Company
Intensity an...
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OE is a complex interplay of
multiple factors...
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Big ...
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Suppliers and technologies in the context of ...
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Big Data – Challenges towards Data Value
Big ...
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Multimedia dominates
Prof. Dr. Stefan Wrobel ...
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Types of Data in Companies
Structured, Semist...
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The data iceberg
Database tables
Excel spread...
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Big ...
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Data sources and origin in companies
Internal...
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The Linked Open Data Universe
Prof. Dr. Stefa...
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Big Data – Challenges towards Data Value
Big ...
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Case study: privacy attitudes in Germany
62Pe...
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Roadblocks seen in survey
• Companies see the...
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Big ...
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bu...
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Big ...
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Example National Health Service
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EDF2014: Stefan Wrobel, Institute Director, Fraunhofer IAIS / Member of the board of BITKOM working group Big Data: The Value of Big Data - From Data-Driven Enterprises to a Data-driven Economy

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Opening Keynote by Stefan Wrobel, Institute Director, Fraunhofer IAIS / Member of the board of BITKOM working group Big Data at the European Data Forum 2014, 19 March 2014 in Athens, Greece: Value of Big Data - From Data-Driven Enterprises to a Data-driven Economy

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EDF2014: Stefan Wrobel, Institute Director, Fraunhofer IAIS / Member of the board of BITKOM working group Big Data: The Value of Big Data - From Data-Driven Enterprises to a Data-driven Economy

  1. 1. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS The Value of Big Data From Data-Driven Enterprises to a Data-driven Economy Prof. Dr. Stefan Wrobel Fraunhofer-Institute for Intelligent Analysis and Information Systems IAIS Fraunhofer Alliance Big Data www.iais.fraunhofer.de bigdata.fraunhofer.de Prof. Dr. Stefan Wrobel This presentation contains copyrighted material and may not be reproduced without permission © Fraunhofer, 2014
  2. 2. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Fraunhofer IAIS: Intelligent Analysis and Information Systems Do more with data 2Prof. Dr. Stefan Wrobel 200 people, at the campus Birlinghoven castle close to Bonn Research areas  Data Science and Big Data  Data Linking, Open Data  Machine Learning, Data Mining, Multimedia Pattern Recognition, Sensor Analytics  Visual Analytics  Big data in business processes
  3. 3. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Prof. Dr. Stefan Wrobel 3
  4. 4. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Fraunhofer Alliance Big Data Joint competences in a »Big Data Factory« for Germany Strategies, Solutions and Successes 24 Fraunhofer institutes – one central coordination point Synchronized and broad competence portfolio with many years of expertise in big data in different sectors Best of class Big Data solutions for individual projects, consulting and qualification of personnel bigdata.fraunhofer.de Contact: Prof. Dr. Stefan Wrobel (Chairman)
  5. 5. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Prof. Dr. Stefan Wrobel 5 (Germany)
  6. 6. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS User Content www. Open Data Big Data Trends Convergence Ubiquitous Intelligent Systems
  7. 7. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS User Content www. Open Data Big Data Trends Convergence Ubiquitous Intelligent Systems 40 Zettabyte by 2020 [IDC 2012]
  8. 8. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data A definition attempt Big Data in general refers to  The trend towards availabity of ever more detail than ever closer to realtime data  The switch from a model-driven to a model- and data-driven approach  The economic potentials that result from the analysis and use of big data when properly integrated into company processes Big Data currently focuses technically on the following aspects  Volume, Variety, Velocity  In-memory computing, Hadoop etc.  Real-time analysis and effects of scale Big Data must take implications to society into account Prof. Dr. Stefan Wrobel 8
  9. 9. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data The view of BITKOM, The German IT Association Prof. Dr. Stefan Wrobel 9 Source: BITKOM Big Data Leitfaden, 2012. BITKOM AK Big Data Volume Variety AnalyticsVelocity Number of records and files Yottabytes Zettabytes Exabytes Petabytes Terabytes External data (web open data, etc.) Company data Unstructured, semistructured, structured data Presentations | text | video | images | tweets | blogs Machine to machine communication Discovery of relationships, patterns, meaning Prediction models Data Mining Text Mining Image Analytics | Visualization | Realtime High speed data generation Constant transmission of generated Data in realtime Milliseconds Seconds | minutes | hours Big Data
  10. 10. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Sources/©: http://m.sybase.com/detail?id=1095954 und McKinsey Studie, 2011
  11. 11. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Innovation study Big Data Desk research (current state of affairs) In-depth workshops for industry sectors (qualitative study) Online survey (quantitative study) 11Prof. Dr. Stefan Wrobel  Detailed overview of the national and international Big Data landscape  More than 50 systematic Big Data Business Cases  Expert workshops  Finance, Telecom, Market research, E- Comm., Insurance  1.10.2012 to 30.11.2012  82 high-ranking executives from small and large companies
  12. 12. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data Competitive Edge Prof. Dr. Stefan Wrobel 12 [Sources/©: MIT Sloan Management Review 2012, 400 companies]
  13. 13. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data Uptake Worldwide U.S. Ahead, Europe Coming Prof. Dr. Stefan Wrobel 13 [Sources/©: TCS 2013 Trend Study Big Data, 643 companies]
  14. 14. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data ROI Very positive ROIs across all regions Prof. Dr. Stefan Wrobel 14 [Sources/©: TCS 2013 Trend Study Big Data, 643 companies]
  15. 15. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data Efforts Will Increase Comparison of Actual Volume 2012 with Projected Volume 2015 Prof. Dr. Stefan Wrobel 15 [Sources/©: TCS 2013 Trend Study Big Data, 643 companies]
  16. 16. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Use Of Big Data in Company Functions From controlling to research Prof. Dr. Stefan Wrobel 16 [Source/© BARC Big Data Survey Europe 2013, 274 Europ. Companies]
  17. 17. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Published Success Stories Across all Sectors 17Prof. Dr. Stefan Wrobel 17
  18. 18. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Fraunhofer alliance projects across all sectors Highlights Life Sciences & Health Care Logistics & Mobility Security Business & Finance Energy & Environmt Production & Industry 4.0
  19. 19. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data Comprehensive Strategies Rare Only few companies have comprehensive strategies Prof. Dr. Stefan Wrobel 19 [BARC Big Data Survey Europe ©2013, 274 Companies] [BITKOM Big Data Survey Germany ©2014, 507 Companies]
  20. 20. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Barriers to Big Data in Companies Prof. Dr. Stefan Wrobel 20 [BITKOM Big Data Survey Germany ©2014, 507 Companies, transl. SW] Too few big data specialists Technical IT Security Requirements Insufficient Budget Privacy Regulations are a barrier Big Data Tools/Solutions are not sufficiently mature yet I know of too few supplier of big data solutions We don‘t have enough data I don‘t know of sufficiently many usage areas Our data are of insufficient quality
  21. 21. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  22. 22. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  23. 23. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data and the Digital Company Intensity and Leadership! Prof. Dr. Stefan Wrobel 23 DigitalIntensity Transformation Management Intensity DigitalIntensity Transformation Management Intensity DigitalIntensity Transformation Management Intensity Revenue Revenue/Employee Fixed Assets Turnover Profitability EBIT Margin Net Profit Margin Market Valuation Tobin’s Q Ratio Price/Book Ratio [MIT Sloan Management Review ©2012]
  24. 24. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS OE is a complex interplay of multiple factors  Who do we want to be?  What are we offering?  How are we organized?  What is our style of working?  What is our common understanding?  How do we optimally use our means?  … Whenever too few factors are being considered, a lot of potential is lost Operational Excellence Big Data as a Key Enabler 24 Strategy Products Organisation Processes Culture Asset Goals and Guiding Lines Processes Inside
  25. 25. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  26. 26. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Suppliers and technologies in the context of Big Data (Selection) [© trademark holders]
  27. 27. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  28. 28. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Multimedia dominates Prof. Dr. Stefan Wrobel 28
  29. 29. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Types of Data in Companies Structured, Semistructured, Unstructured Prof. Dr. Stefan Wrobel 29 [TCS ©2013 Trend Study Big Data, 643 companies]
  30. 30. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS The data iceberg Database tables Excel spreadsheets Other data with fixed structure Email, Notes Word documents PDF. Power Point Other text Images Video, audio 20% 80%
  31. 31. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  32. 32. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Data sources and origin in companies Internal vs External Prof. Dr. Stefan Wrobel 32 [TCS ©2013 Trend Study Big Data, 643 companies]
  33. 33. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS The Linked Open Data Universe Prof. Dr. Stefan Wrobel 33 © lod-cloud.net Est. 50 billion facts 2013
  34. 34. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  35. 35. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Case study: privacy attitudes in Germany 62Percent want better privacy protection 87Percent believe that companies are using data beyond what is publicly annouced 95Percent pay attention to whom they give their data 80Percent sold their data for 5 € in a lab setting 10Percent ready to give their data in social web for coupons 50Percent read the general terms and conditions and privacy rules 75Percent would provide them for medical good 10Percent would give data for personalized recommendations [Handelsblatt Research Institute 2013]
  36. 36. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Roadblocks seen in survey • Companies see the main challenges in the following areas: • Privacy and security (49%) • Budgets and priorities (45%) • Technical challenges of data management and analytics(38%) • Expertise (36%) • Lack of familiarity with big data technologies (35%). • To address these issues, 95% of companies requested • Best Practices, Trainings, Supplier and solution catalogues and better privacy lawas and regulation 36
  37. 37. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  38. 38. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Data Scientists From data and analytics to business Prof. Dr. Stefan Wrobel 38 Data Scientist Understanding of business goals and relation to analytics Solid fundamentals in data-driven modeling and analytical methods Capability of identifying and linking data sources Command of necessary algorithms and toolsEngineering knowledge about feasibility, scalability, cost Responsibility, Leadership, Networking Judgment about values, norms, regulations Communicative talent to translate into business world
  39. 39. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Big Data – Challenges towards Data Value Big Data is not an isolated IT topic, but must address business value end-to-end in company/sector specific ways Technical solutions must be designed-to-fit Further innovation needs beyond off-the-shelf software Data Linking and brokering need open standards Security and Privacy are demanded by business and society alike – „by design“ Enormous education and training needs SMEs and startups face special challenges and need a supportive ecosystem Prof. Dr. Stefan Wrobel From data-driven companies to a data-driven economy
  40. 40. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Example National Health Service The benefits of a working open data ecosystem NHS provides enormous datasets:  Hospital Episode Statistics (HES) repository: 100 million records per year (outpatient appointments, A&E attendances, hospital admissions)  Prescription data: 500 Million records per year, increasingly openly available Success story:  Analysis of Statin prescriptions 2011-12 (37 Million records) by a team of Mastodon C, Open Health Care UK and BadScience.net  Annual savings of more than 200 Mio Pounds identified (equally effective medications) Prof. Dr. Stefan Wrobel 40 [Guardian, theodi.org, prescribinganalytics.com, wikimedia, 2013]
  41. 41. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Returning the value of data Prof. Dr. Stefan Wrobel An interesting experiment in the U.S. [www.datacoup.com, March ©2014]  8 $/month  1500 beta users
  42. 42. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Data as a Product Is it worth selling? Prof. Dr. Stefan Wrobel 42 [TCS ©2013 Trend Study Big Data, 643 companies]
  43. 43. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Dimensions of the big data ecosystem Prof. Dr. Stefan Wrobel [Cavanillas, Markl, May, Platte, Urban, Wahlster, Wrobel – Big Data Value (Draft), 2014]
  44. 44. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Smart Data Innovation Lab A nationwide industry-research plattform for big data value 44 [S. Fischer, SAP/SDIL, ©2014]
  45. 45. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Creating a European Big Data Ecosystem Prof. Dr. Stefan Wrobel A Partnership of multiple stakeholders will be needed Big Data Value Ecosystem Big Data Vendors Public and corporate users SMEs and startups Researche rs Policy Makers
  46. 46. © Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS Conclusion  Big Data is here to stay: significant uptake in companies  Enormous potential and growth expected  Significant barriers exist: the big 7 challenges  Business value, designed-to-fit, innovation, data linking, privacy, education, SMEs  Coordinated action by multiple stakeholders at European level needed Prof. Dr. Stefan Wrobel 46 [Guardian, theodi.org, prescribinganalytics.com, wikimedia, 2013]

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