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SENTIENT ENTERPRISE

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Humans are sentient. We perceive. We feel. We listen. The problem is the more you put together, the more we lose these capabilities. We get slower. The idea is, how we create a company that acts like a single organism, where we identify opportunities, and that allows us to work in a faster and exponential world world where development happens in months rather than years. Don't let digital transformation become a war of competitive attrition. You may need to invest in your future to change the game.

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SENTIENT ENTERPRISE

  1. 1. SENTIENT ENTERPRISE CHRIS TWOGOOD | Teradata
  2. 2. “Today Digitalization delivers every single car on the road today as a device”
  3. 3. @ r a t z e s b e r g e r
  4. 4. @ r a t z e s b e r g e r Data Graphic: d3js.org SELF SERVICE EVERYTHING
  5. 5. MyMagic+ leveraging data and analytics to improve guest experiences
  6. 6. $70 BILLION APP ECONOMY 7Source: http://venturebeat.com/2014/04/29/mobile-apps-could-hit-70b-in-revenues-by-2017-as-non-game-categories-take-off/
  7. 7. SENTIENT ENTERPRISE
  8. 8. SHARE SEARCH DESIGN INTERACT ANALYZE KNOW IDENTIFY DISCOVER ACOMPANYASA SINGLE ORGANISM
  9. 9. 2 3 1 FIVE STAGES The agile data platform moves traditional central DW structures to a balanced decentralized framework built for agility. 5 4
  10. 10. EMPTY SANDBOX ORIGINAL DATA DATA DUPLICATED IN DATA SILO 2X DUPLICATED DATA BY USER1 USER2 ANALYZING THE OLD DATA
  11. 11. EFFICIENT SANDBOX Security Governance Privacy Dev Ops Data Management Data Access … RECORDI ALL ACTI
  12. 12. ““All sensor data from multiple airlines entire fleet for years - trillions of records - 60-80x more efficient on storage and queries” Patent Application Published May 5, 2016
  13. 13. 2 3 1 5 4 FIVE STAGES From transactional to behavioral data. Value comes from behaviors rather than transactions.
  14. 14. TRANSACTIONAL DATA
  15. 15. 10 to 100X HIGHER DATA VOLUMES BEHAVIORAL DATA BEHAVIORAL PATTERNS
  16. 16. CUSTOMER BEHAVIOR GUSTS SQUALLS WINDS MACHINE BEHAVIOR Low level short duration turbine directional changes Medium level turbine directional changes Highest turbine directional changes AIR DENSITY & AIR TEMPERATURE
  17. 17. CUSTOMER BEHAVIOR All readings are analyzed to get the optimal pitch on the blades Hydraulic measurements Wind power capacity Gearbox readings Wind speed at hubs Turbine brakes quality Sensor data that is collected from the wind parks GUSTS SQUALLS WINDS MACHINE BEHAVIOR AIR DENSITY & AIR TEMPERATURE Low level short duration turbine directional changes Medium level turbine directional changes The most turbine directional changes
  18. 18. “ Guarantee if they’re delayed more than 15 minutes, they pay you back the whole ticket ” Gerhard Kress Siemens Spokesman
  19. 19. MACHINE BEHAVIOR CUSTOMER BEHAVIOR CUSTOMER BEHAVIOR CUSTOMER BEHAVIOR MACHINE BEHAVIOR CUSTOMER BEHAVIOR CUSTOMER BEHAVIOR MACHINE BEHAVIOR SANDBOX SANDBOX SANDBOX SANDBOX SANDBOX SANDBOX
  20. 20. MACHINE BEHAVIOR MACHINE BEHAVIOR CUSTOMER BEHAVIOR MACHINE BEHAVIOR SANDBOX SANDBOX SANDBOX MACHINE BEHAVIOR CUSTOMER BEHAVIOR SANDBOX CUSTOMER BEHAVIOR
  21. 21. FIVE STAGES 1 5 4 LinkedIn for analytics. From centralized metadata to crowd-sourced collaboration. Social interactions connect the data within the enterprise. 3 2
  22. 22. Collaboration
  23. 23. Storytelling
  24. 24. SHARE LIKE SEARCH DESIGN INTERACT ANALYZE COLLABORATE
  25. 25. 1 2 3 5 4 FIVE STAGES Analytical apps. From static applications and ETL to agile self-service apps. From extraction of data to enterprise listening.
  26. 26. STRESS FREE IT
  27. 27. app APP DEPLOY APP FRAMEWORK app APP IDEA FROM A NON-EXPERT app HOUR 1 HOUR 2 HOUR 3 HOUR 4 HOUR 5 HOUR 6 HOUR 7 HOUR 8 HOUR 9 HOUR 10
  28. 28. FIVE STAGES 1 2 3 5 4 Predictive technologies and algorithms. From focusing only 10% of time on decision making and 90% on sifting through data, to 90% on decision making with the help of automated algorithms.
  29. 29. TIME WASTED SIFTING THROUGH DATA 90% Messy Data KPIs INTERSECTIONS PRODUCT CATEGORIES AGGREGATIONS SOCIAL MEDIA SOCIAL MEDIA SALES AUTOMATION MOBILE OPTIMIZATION SEO TESTING INTEGRATION
  30. 30. INTEGRATION ALGORITHMIC APPS TIME SPENT ON DECISION MAKING 90 Data Presented Simply Cleansing and refining sources identifying signals and patterns Messy Data %
  31. 31. DECISION MAKING BY HUMANS ALGORITHMS - PATTERN ANALYTICS
  32. 32. Focus on a behavior-centric mindset 1 2 3 Drive agility in organization Deliver automation at scale
  33. 33. @ r a t z e s b e r g e r Thank you

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