Big Data In Practice (Use Cases) - How 45 Successful Companies Used Big Data Analytics To Deliver Extraordinary Results

All cases will be based on the author’s direct insights with the companies listed – these are all organisations which he has either consulted for or been granted access to direct interviews, and have endorsed their inclusion in the book.

All chapters will follow a similar structure so that the reader can scan the various sections to quickly find the information they are after.

Chapter structure:

• Background
  • A brief overview of the company and context of the case study
  • What Problem Is Big Data Helping To Solve?
    • A description of what business problem / or issues big data is helping to solve in this case study company.
    • How Is Big Data Used In Practice?
      • An outline of how big data was applied in this case example. Outlining the implementation, where the data came from, how it was analysed, what algorithms were developed.
      • What Where The Results?
        • A description of the benefits / insights gained and the value of these.
        • What Data Was Used?
          • A description of what data was used (external, internal, quantities, structured, unstructured, sources)
          • What Are The Technical Details?
            • A description of the technical details – e.g. where was the data stored (cloud, hadoop clusters, data lakes) and what where the specifics (programming languages such as Spark or Python) and vendor details.
            • Any Challenges That Had To Be Overcome?
              • Explaining the key project challenges, where applicable and available. E.g. consolidating the data, selling the project, acquiring the right skills, finding the data, etc.)
              • What Are The Key Learning Points And Take Aways?
                • A comment section where I highlight the key learning points from this case study and any generic take aways that should be relevant to others.
                • References And Further Reading
                  • Any references and links to further reading material.

Case Study Companies

Here is a list of potential case studies I would include, but this list will be fluid and is highly likely to change as new and interesting cases develop over the next few months.

1. Amazon – How predictive analytics are used to get a 360 degree view of customers
2. Apple – How Apple puts big data at the center of their business
3. Dickey’s Barbecue Pit – How big data is used to gain performance insights in one of America’s most successful restaurant chains
4. Rolls-Royce – how big data is used to drive success in manufacturing
5. Shell – how big data is used in big oil companies
6. Transport for London – how big data is used to improve and manage public transport in London
7. Milton Keynes City – how big data is used to create smarter cities
8. Walmart – how big data is used to drive supermarket performance
9. U.S. Olympic Women’s Cycling Team – how big data analytics is used to optimize athletes’ performance

10. Microsoft – how big data is central to Microsoft’s success

11. Facebook – how Facebook used big data to understand consumers

12. John Deere – how big data can be applied on farms

13. LinkedIn – how big data is used to fuel social media success

14. Uber – how big data is at the center of Uber’s transportation business

15. US Immigration – how big data is used to keep passengers safe and prevent terrorism

16. Acxiom – how big data is used to profile all of us

17. Manchester United Football Club – how big data is used to optimize the beautiful game

18. Netflix – how Netflix used big data to give us the programs we want

19. Twitter – how Twitter together with IBM deliver customer insights from big data

20. U.S. Government – how big data is applied in the government sector

21. Google – how big data is at the heart of Google’s business model

22. Nest (Google) – how big data is transforming the thermostat industry

23. Palantir – how big data is used to help the CIA and detect bombs in Afghanistan

24. Flatiron Health – Using big data to fight cancer

25. AirBnB – how big data is used to disrupt the hospitality industry

26. GE – how big data is fuelling the industrial internet at GE

27. ETSY – how big data is used in a crafty way

28. Red Bull Racing – how big data is essential to the success of F1 teams

29. Narrative Science – how big data is used to challenge journalists

30. Ralf Lauren – Big Data in the fashion industry

31. Zynga – Big data in the gaming industry

32. Airbus – how big data is used in the airline industry

33. Target – the challenges of understanding customers

34. Fitbit – big data in the personal fitness arena

35. BBC – How big data is applied in the media

36. Cornerstone OnDemand – Crunching employee data to predict performance

37. IMB Watson – using big data analytics to gain answers to anything

38. CERN – crunching big data to reveal the secrets of our universe

39. Kaggle – crowed sourcing your data scientist

40. FBI – big data in the police and law enforcement

41. TerraSeismic – Using big data to predict earth quakes

42. Capital One – How big data is used in Banking

43. Visa – how big data is used to detect fraud

44. Autodesk – how big data is transforming the software industry

45. Caesars Entertainment – when big data becomes your 1billion Dollar asset

The author may swap in some more SME examples once confirmed.

BERNARD MARR is a bestselling business author, keynote speaker and consultant in Big Data analytics and enterprise performance. He is one of the world's most highly respected thought leaders on data in business and regularly helps major companies and governments gain better insights from their data. Bernard is a frequent contributor to the World Economic Forum, writes a regular column for Forbes, and is recognized by LinkedIn as one of the world's top 5 business influencers. He is the author of numerous books including Big Data (winner of the Futures Category at the CMI Management Book of the Year Awards 2016), Big Data for Small Business For Dummies and Key Business Analytics.