How to transform data into dollars this is always about Business Intelligence

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2 Swiss BI Day - 03/04/2014! How to transform data into dollars this is always about Business Intelligence! Philippe Nieuwbourg philippe.nieuwbourg@decideo.com

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6 A lot of things in common between oil and data

7 Prospecting Mine Collect Transport Store Oil and Data

8 Refine to create value

9 (Volume + Velocity + Variety)

10 Volume

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12 Velocity

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14 Variety

15 From structured to unstructured data Structured data Figures, lists of data, meta-data SQL (or Hadoop for very high volume) Semi-structured data XML Unstructured data Content of texts, photos, audio files, videos NoSQL, Hadoop Patents, s, books, postal addresses

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18 (Volume + Velocity + Variety) x Visualization = Value

19 BUSINESS CASES

20 Case study : M&A detection

21 Facts When a M&A operation is ongoing, people from both company prepare their future by connecting together The relative value of connections between both companies is growing How could we detect that?! Because a growing rate of daily connections between people from two companies could be a M&A signal

22 LinkedIn InMaps visualization Understand your network

23 DataPerformers Research project initiated ay UQAM (Montréal) Based on LinkedIn APIs Collect data Developp models and algorithms to detect signals Anticipate -> Machine learning

24 Retail Case study: Where will be my customers in 5 years

25 Retail banking information available for market studies

26 Predictive analysis Transaction Analysis Trends modelization Create links between consumers and production Population trends analysis! Your bank will become a data provider Or a data provider could become a bank

27 TopShop : try, store, analyze

28 Case study: Tax optimization

29 How to identify pool owners who didn t declare their pool and didn t pay the right tax Data: Aerial photos Land registry

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32 Project steps Digitalize photos Identifiy pools -> means «create structured data based on aerial photos» Compare these data with land registry Just print the list and send the letters ROI in just a couple of minutes! And can be repeated every year

33 Case study: Industrial Maintenance

34 Share knowledge between users Collect data on industrial equipments Anonymize data Plan failures, repair before it fails Share between all users to model better prediction

35 Case study: Car industry

36 Cars will be the main Big Data Platform Beginning today!

37 Technology exists Today

38 Chevrolet Volt Tomorrow hundreds of IP addresses

39 And tomorrow, which company will invest? Insurance companies Railways companies States... which company will create a business model based on these data?

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41 Case study: From smart house to smart cities

42 INTERNET OF THINGS Permanent connection, permanent data generation! Houses, cars, shops, restaurants, streets...! Imagine business models that will collect, analyze and create value from these data! How much are you ready to pay for it

43 SMART CITY Security, services, energy savings, citizen oriented city

44 Let s talk about Hockey

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47 With a little bit of imagination Today: Create a direct link between the brand and the consumers Communicate with the consumers Every single goal -> Let s have a drink to celebrate!! Tomorrow: Advertising push Generate feedback Analyze Optimize advertising and sponsorship Extend to other sports

48 Case study: Quantified self

49 Let me introduce you to Nicholas Felton

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51 Daytum for all QS fans

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53 HAPIFORK The 1st connected fork! Eat slowly to eat better! Collect and share! It s your turn to imagine business models based on that data...

54 And tomorrow... We could use these data for marketing purpose Connect to healthcare management system Personalization of insurance quotation Control Hiring...

55 IWATCH... BUT WHAT? 21 % of American people already track one health KPI (sleep, glucose rate, pulse, exercice )! Do you really think the iwatch will just show time, agenda and ????

56 BODIES DATA ETL HumanAPI.co

57 BUSINESS INTELLIGENCE MARKET AGES

58 BI Architecture Evolution Business Intelligence / Data Warehouse Reporting OLAP Business Analytics / Business Discovery Predictive analysis Connexion to operational processes Big Data / Data Lakes Real time analysis of external data Social Media analysis Embed in external processes

59 BIG DATA TOOLS

60 WHAT S NEW? ETL Real time collection, Event processing, Speed STORAGE InMemory, NoSQL, Hadoop, and perhaps «HANA revolution» ANALYSIS Predictive models embedded inside operational processes PUBLICATION TOOLS Data Visualization, Data Storytelling

61 5 STEPS TO TAKEAWAY

62 1 - Identify and reference available or collectable data

63 2 - Imagine how you could transform your business! Go behind your limits!

64 3 - Mix offered services and collected data

65 4 - Business Model workshop

66 Go or no go!

67 5 - If you decide to go: prototyping, iteration, always limit risk

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69 Last question: Data Scientist myth or reality?

70 The Data Scientist Cocktail IT: New databases, agility in dataset extraction and manipulation! Statistics: ability to create models, data analysis, predictive analysis! Communication: data visualization, data storytelling

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