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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.
- Amazon – How predictive analytics are used to get a 360 degree view of customers
- Apple – How Apple puts big data at the center of their business
- Dickey’s Barbecue Pit – How big data is used to gain performance insights in one of America’s most successful restaurant chains
- Rolls-Royce – how big data is used to drive success in manufacturing
- Shell – how big data is used in big oil companies
- Transport for London – how big data is used to improve and manage public transport in London
- Milton Keynes City – how big data is used to create smarter cities
- Walmart – how big data is used to drive supermarket performance
- 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
- Titolo del Libro in lingua: Big Data in Practice
- Sottotitolo: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results
- Lingua: English
- Autore: Bernard Marr
- Editore: John Wiley & Sons Inc
- Collana: John Wiley & Sons Inc (Hardcover)
- Data di Pubblicazione: 02 Maggio '16
- Genere: BUSINESS and ECONOMICS
- Argomenti : Consumer behavior Strategic planning Big data
- Pagine: 308
- Peso gr: 520
- Dimensioni mm: 228 x 152 x 25
- ISBN-10: 1119231388
- EAN-13: 9781119231387