MARC details
| 000 -LEADER |
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| fixed length control field |
05793cam a2200289 i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
MIUC |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20200221104055.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
160129s2016 nju b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781119231387 |
| Qualifying information |
hardback |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
DLC |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| Description conventions |
rda |
| Modifying agency |
DLC |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
658.4038 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Marr, Bernard |
| 9 (RLIN) |
3228 |
| 952 ## - Items |
|---|
| Itemnumber |
1769 |
| 245 10 - TITLE STATEMENT |
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| Title |
Big data in practice : |
| Remainder of title |
how 45 successful companies used big data analytics to deliver extraordinary results / |
| Statement of responsibility, etc. |
Bernard Marr. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Chichester, West Sussex : |
| Name of producer, publisher, distributor, manufacturer |
Wiley, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2016. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xi, 308 pages ; |
| Dimensions |
22 cm |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Source |
rdacontent |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Introduction -- <br/>Ch. 1. Walmart: How Big Data Is Used To Drive Supermarket Performance -- <br/>Ch. 2 CERN: Unravelling the Secrets of the Universe with Big Data -- <br/>Ch. 3. Netflix: How Netflix Used Big Data to Give Us the Programmes We Want -- <br/>Ch. 4. Rolls-Royce: How Big Data Is Used To Drive Success In Manufacturing -- <br/>Ch. 5. Shell: How Big Oil Uses Big Data -- <br/>Ch. 6. Apixio: How Big Data Is Transforming Healthcare -- <br/>Ch. 7. Lotus F1 Team: How Big Data Is Essential To The Success Of Motorsport Teams -- <br/>Ch. 8. Pendleton & Son Butchers: Big Data for Small Business -- <br/>Ch. 9. US Olympic Women's Cycling Team: How Big Data Analytics Is Used To Optimize Athletes' Performance -- <br/>Ch. 10. ZSL: Big Data In The Zoo And To Protect Animals -- <br/>Ch. 11. Facebook: How Facebook Use Big Data to Understand Customers -- <br/>Ch. 12. John Deere: How Big Data Can Be Applied On Farms -- <br/>Ch. 13. Royal Bank of Scotland: Using Big Data to Make Customer Service More Personal -- <br/>Ch. 14. LinkedIn: How Big Data Is Used To Fuel Social Media Success -- <br/>Ch. 15. Microsoft: Bringing Big Data To The Masses -- <br/>Ch. 16. Acxiom: Fuelling Marketing With Big Data -- <br/>Ch. 17. US Immigration and Customs: How Big Data Is Used To Keep Passengers Safe and Prevent Terrorism -- <br/>Ch. 18. Nest: Bringing the Internet of Things into The Home -- <br/>Ch. 19. GE: How Big Data Is Fuelling the Industrial Internet -- <br/>Ch. 20. Etsy: How Big Data Is Used In A Crafty Way -- <br/>Ch. 21. Narrative Science: How Big Data Is Used To Tell Stories -- <br/>Ch. 22. BBC: How Big Data Is Used In The Media -- <br/>Ch. 23. Milton Keynes: How Big Data Is Used To Create Smarter Cities -- <br/>Ch. 24. Palantir: How Big Data Is Used To Help The CIA And To Detect Bombs In Afghanistan -- <br/>Ch. 25. Airbnb: How Big Data Is Used To Disrupt the Hospitality Industry -- <br/>Ch. 26. Sprint: Profiling Audiences Using Mobile Network Data -- <br/>Ch. 27. Dickey's Barbecue Pit: How Big Data Is Used to Gain Performance Insights Into One Of America's Most Successful Restaurant Chains -- <br/>Ch. 28. Caesars: Big Data At The Casino -- <br/>Ch. 29. Fitbit: Big Data In The Personal Fitness Arena -- <br/>Ch. 30. Ralph Lauren: Big Data In The Fashion Industry -- <br/>Ch. 31. Zynga: Big Data In The Gaming Industry -- <br/>Ch. 32. Autodesk: How Big Data Is Transforming The Software Industry -- <br/>Ch. 33. Walt Disney Parks and Resorts: How Big Data Is Transforming Our Family Holidays -- <br/>Ch. 34. Experian: Using Big Data To Make Lending Decisions And To Crack Down On Identity Fraud -- <br/>Ch. 35. Transport for London: How Big Data Is Used To Improve And Manage Public Transport In London -- <br/>Ch. 36. The US Government: Using Big Data To Run A Country -- <br/>Ch. 37. IBM Watson: Teaching Computers To Understand And Learn -- <br/>Ch. 38. Google: How Big Data Is At The Heart Of Google's Business Model -- <br/>Ch. 39. Terra Seismic: Using Big Data To Predict Earthquakes -- <br/>Ch. 40. Apple: How Big Data Is At The Centre Of Their Business -- <br/>Ch. 41. Twitter: How Twitter And IBM Deliver Customer Insights From Big Data -- <br/>Ch. 42. Uber: How Big Data Is At The Centre Of Uber's Transportation Business -- <br/>Ch. 43. Electronic Arts: Big Data In Video Gaming -- <br/>Ch. 44. Kaggle: Crowdsourcing Your Data Scientist -- <br/>Ch. 45 Amazon: How Predictive Analytics Are Used To Get A 360-Degree View Of Consumers. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Consumer behavior. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Strategic planning |
| 9 (RLIN) |
877 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Big data |
| 9 (RLIN) |
1863 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Knowledge management |
| 9 (RLIN) |
3229 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Consumer behavior |
| 9 (RLIN) |
438 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Online version: |
| Main entry heading |
Marr, Bernard, author. |
| Title |
Big data in practice |
| Place, publisher, and date of publication |
Hoboken : Wiley, 2016 |
| International Standard Book Number |
9781119231417 |
| Record control number |
(DLC) 2016010994 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
