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SENTIENT ENTERPRISE
The document discusses the concept of a 'sentient enterprise' driven by digitalization and agile data platforms, emphasizing the shift from traditional data warehousing to decentralized frameworks for enhanced agility. It highlights the importance of behavioral data over transactional data, detailing how analyzing customer and machine behaviors can lead to improved decision-making and efficiency. Additionally, it covers the evolution of analytics from static applications to agile, self-service apps enabled by predictive technologies and algorithms.
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SENTIENT ENTERPRISE
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- 3. “Today Digitalization delivers everysingle car on the road today as a device”
- 5. @ r at z e s b e r g e r
- 6. @ r at z e s b e r g e r Data Graphic: d3js.org SELF SERVICE EVERYTHING
- 8. MyMagic+ leveraging data andanalytics to improve guest experiences
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- 12. 2 3 1 FIVE STAGES The agiledata platform moves traditional central DW structures to a balanced decentralized framework built for agility. 5 4
- 13. EMPTY SANDBOX ORIGINAL DATA DATA DUPLICATED IN DATASILO 2X DUPLICATED DATA BY USER1 USER2 ANALYZING THE OLD DATA
- 14. EFFICIENT SANDBOX Security Governance Privacy Dev Ops Data Management DataAccess … RECORDI ALL ACTI
- 16. ““All sensor datafrom multiple airlines entire fleet for years - trillions of records - 60-80x more efficient on storage and queries” Patent Application Published May 5, 2016
- 17. 2 3 1 5 4 FIVE STAGES From transactionalto behavioral data. Value comes from behaviors rather than transactions.
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- 19. 10 to 100X HIGHERDATA VOLUMES BEHAVIORAL DATA BEHAVIORAL PATTERNS
- 20. CUSTOMER BEHAVIOR GUSTS SQUALLS WINDS MACHINE BEHAVIOR Lowlevel short duration turbine directional changes Medium level turbine directional changes Highest turbine directional changes AIR DENSITY & AIR TEMPERATURE
- 21. CUSTOMER BEHAVIOR All readingsare 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
- 23. “ Guarantee ifthey’re delayed more than 15 minutes, they pay you back the whole ticket ” Gerhard Kress Siemens Spokesman
- 24. MACHINE BEHAVIOR CUSTOMER BEHAVIOR CUSTOMERBEHAVIOR CUSTOMER BEHAVIOR MACHINE BEHAVIOR CUSTOMER BEHAVIOR CUSTOMER BEHAVIOR MACHINE BEHAVIOR SANDBOX SANDBOX SANDBOX SANDBOX SANDBOX SANDBOX
- 25. MACHINE BEHAVIOR MACHINE BEHAVIOR CUSTOMERBEHAVIOR MACHINE BEHAVIOR SANDBOX SANDBOX SANDBOX MACHINE BEHAVIOR CUSTOMER BEHAVIOR SANDBOX CUSTOMER BEHAVIOR
- 26. FIVE STAGES 1 5 4 LinkedIn foranalytics. From centralized metadata to crowd-sourced collaboration. Social interactions connect the data within the enterprise. 3 2
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- 30. 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.
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- 32. app APP DEPLOY APP FRAMEWORK app APP IDEA FROM ANON-EXPERT app HOUR 1 HOUR 2 HOUR 3 HOUR 4 HOUR 5 HOUR 6 HOUR 7 HOUR 8 HOUR 9 HOUR 10
- 33. FIVE STAGES 1 2 3 5 4 Predictive technologiesand 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.
- 34. TIME WASTED SIFTING THROUGHDATA 90% Messy Data KPIs INTERSECTIONS PRODUCT CATEGORIES AGGREGATIONS SOCIAL MEDIA SOCIAL MEDIA SALES AUTOMATION MOBILE OPTIMIZATION SEO TESTING INTEGRATION
- 35. INTEGRATION ALGORITHMIC APPS TIME SPENT ON DECISIONMAKING 90 Data Presented Simply Cleansing and refining sources identifying signals and patterns Messy Data %
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- 37. Focus on abehavior-centric mindset 1 2 3 Drive agility in organization Deliver automation at scale
- 38. @ r at z e s b e r g e r Thank you