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Big Data in Practice - 9781119231387

Un libro in lingua di Bernard Marr edito da John Wiley & Sons Inc, 2016

  • € 46.80
  • Il prezzo è variabile in funzione del cambio della valuta d’origine

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.

Informazioni bibliografiche