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My definition to Big Data:

Big Data refers to a huge amount of data, which can be used to find correlations between various things. Data is so big that it doesn't fit to regular structured databases or cannot be handled with regular tools. You have to find alternative way to process big data. Analysis of big data answer question what, not why.

References:

  • David Feinleib - Big Data Bootcamp, What Managers Need to Know to Profit from the Big Data Revolution (ISBN: 978-1-484200-41-4)
  • Peter Lake, Robert Drake - Information Systems Management in the Big Data Era (ISBN: 978-3-319-13502-1)
  • Harsha Srivatsa, Madhu Jagadeesh, Soumendra Mohanty - Big Data Imperatives: Enterprise 'Big Data' Warehouse, 'BI' Implementations and Analytics

Ethics in Big Data:

Principles:

  • Be Clear and Concise
  • Give Users Power Over their Data
  • Communicate Value
  • The Importance of Security
  • Building In Privacy

Reference: http://csce.uark.edu/~cwt/COURSES/2014-01--CSCE-4543--SW-ARCH/03--CHAPTERS/Chapter%2020--Ethics%20of%20Big%20Data--Rothmeyer.pdf

My Coursera course diploma:

Exam Questions

Big Data

1. Explain big data and tell how humans thinking should change when discussing about big data?

  • This is the basis of the book. If reader doesn't have any clue of this, he/she hasn't read the book.

2. What are the biggest risks of big data?

  • Dark side of the mighty big data.

The New Killer Apps

3. What are the 8 rules on how innovation process should run within a company and explain why they are important?

  • These are the basis of this Killer Apps book, but it's not only important to know what the rules are but it's also important to know why them are important.

4. In innovation process, why it's important to have someone who is questioning the decision making?

  • You might ask something deeper for every of 8 rules explained in the book, but I choose the rule that I was supposed to explain for whole class.