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Big Data Gold Mining

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Stakeholder workshop Mobility of Data Market Austria workshop series - keynote talk by Dominik Rockenschaub of Catalysts (Scrum Master, Agile & IoT Cluster Project Lead) on 13.03.2017 in Linz.

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Big Data Gold Mining

  1. 1. © Catalysts GmbH Big Data Gold Mining Dominik Rockenschaub Scrum Master, Agile & IoT Cluster Project Lead
  2. 2. 2 ⇒ It’s more likely that Trust & Partnership (sharing ideas) leads to better and disruptive business ideas “The electric light did not come from the continuous improvement of candles.” -Oren Harari
  3. 3. Big Data Gold Mining How? Value? Technical Solutions? Costs? Competition (Dis-)Advantage? Investors | Venture Capital | Public Sponsorships (FFG, …) Creativity Techniques (Design Thinking, Brainstorming, Real World Problem Analysis, ….) IoT Cluster | Machine Learning | Big Data Analysis | Data Science | Artificial Intelligence | Predictor | Classifier Trust + Partnership Statistics never lie (!) - It’s all about numbers/patterns/similarities…..
  4. 4. Where do I find “data”? What is (valuable) “data”? How can one “increase value” of data? Is there a standardized data format? …. 4 Data? ⇒ Join the Rapid Prototyping Train
  5. 5. 5 Data Value Chain Identify Data Offer Data Sell Data (optional) Mashup Data Data Science Data Privacy Use Data Use creative techniques to identify data Think of Business Model Check regulations and law before offering data (EU privacy law, Company Terms of Service, …) Defined Interface Defined Update Interval Marketing & Sales required chicken-and-egg problem between data provider and data consumer Combine data products Data Science and Algorithm Experts required Increase value of data Disruptive Business Models Don’t fear Data Sharing! It’s key for innovation and successful Joint Ventures.
  6. 6. 6 Mobility Data Products 1/2 Data Source Data Artifacts Value/Product ÖBB Schedule Train departure and arrival time, train delays Intermodal Travel Route Planning Linz Bus Schedule Live GPS position of public transport Qando mobile App Car Accident Distribution (Statistik Austria 2016) GPS position, accident frequency Safety Products (Collision Detection, Self Driving Cars) (Floating Data of School Children) GPS position (live, planned) Safety Products (Collision Detection, Self Driving Cars) Engine Manufacturing Company “Health status of engine”, engine speed, ... Predictive Maintenance Hyperloop Simulator Flights, Cars, Boats, Taxis, Trucks, Trains Intermodal Travel Route Planning Specific data/product More visionary data/product
  7. 7. 7 More visionary data/product Even More visionary data/product Mobility Data Products 2/2 Data Source Data Artifacts Value/Product Car Fleet Data (VW/POI) GPS Routes Driving Behaviour (acceleration, breaking, …) Driving Logbook, Cross- & Upselling for Car Dealer, OBU products (DiBox, Automatic, …), Predicted Life: “we recommend your dream-car even before you know” “Routenexakte Wettervorhersage” Wiper frequency, GPS position, ABS/ESP frequency, weather data Self Driving Cars Safe Trip App for Car Driver Crash Avoidance for Insurance Companies “Carlytics” (CROSSNG, Carfin,...) “Health state” of car parts Predictive Maintenance (“Repair today and save 100€”) On-Time Parts Production and On-Time Parts Stock Management “PremiumCar” GPS Route, calendar appointments, user identification Enable Premium Car Features (additional speed, hourse power, ….) “I don’t always need 300hp, but when I do, I enjoy it!” Electricity Power Supplier e-car power consumption, charging frequency Life-Long Energy Products at fixed product price (sell car with higher price, includes lifetime energy demand)
  8. 8. Process for (Data) Product Development Idea! and / or Less costly Expensive High risk Low risk Identified Problem Expected Efficiency Improvement Hypothesis defined
  9. 9. Idea! and / or Less costly Expensive High risk Low risk AlgorithmSpecify Solution Process for (Data) Product Development
  10. 10. Idea! and / or Less costly Expensive High risk Low risk How? Data missing! => Test Driven Development required! Specify Solution Testing Process for (Data) Product Development
  11. 11. Idea! and / or Less costly Expensive High risk Low risk Catalysts Examples: Hyperloop VW/POI Steyr Motors ZAMG 4.0 Companies And many more…. Specify Solution Testing With DMA Data With Simulator censored Process for (Data) Product Development
  12. 12. Idea! and / or Less costly Expensive High risk Low risk Specify Solution Testing With DMA Data With Simulator Validate Hypothesis Rapid Prototyping Train Innovation Design Thinking Brainstorming Lean Canvas …. ⇒ Innovation happens right here ;-) Process for (Data) Product Development
  13. 13. Idea! Specify Solution Testing With DMA Data Validate Hypothesis Real World Market Product Development GoLive With Simulatorand / or Less costly Expensive High risk Low risk Process for (Data) Product Development
  14. 14. Building Products based on Data Floating Car Data ESA Satellite Data ZAMG Weather Data € Movement Data Engine Data ÖBB Traffic Data Your Data Routenexakte Wettervorhersage EODC Hyperloop Travel Portal Steyr Motors Predictive Maintenance Your ProductYour Data Mashup May we help you? € € DATA MARKET PLATFORM
  15. 15. 15 Start now: Big Data Gold Mining with Rapid Prototyping Train Image Source: