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Definition of Big Data

Big Data is a term to describe the collection of datasets so large and complex to be analyzed. Big Data is not a new concept but this term is increasingly used to describe the process of capturing, processing, analysing and visualize massive and complex sets of information.

The quantity of data stored all the time nowadays is too big to be handled efficiently with standard IT technologies. The platform, tools and software used for this purpose are called “Big Data technologies”.

The main features and problems connected to handling different types of large data sets are commonly called “the four V”:

  • Volume: The amount of generated data has increased tremendously the past years.
  • Velocity: More and more data are produced and must be collected in shorter time frames.
  • Variety: Different data sources and formats.
  • Value: Data is not only recorded, now data must be also exploited, gathering information must have more than one purpose.

Links

http://www.nessi-europe.com/Files/Private/NESSI_WhitePaper_BigData.pdf

http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation

http://www-01.ibm.com/software/data/bigdata/what-is-big-data.html

Ethics in big data

Why questions about ethics of Big Data are being raised nowadays? The technology itself is inherently ethics-agnostic. But Big Data implies that there is information collected with the following features:

  • The availability of a wide range of data from many sources.
  • The ability to cheaply correlate this data to understand a bigger picture.
  • The accuracy with which an individual can be identified and targeted.
  • The ability to pinpoint someone’s location for contextual insight and surveillance.
  • The application of this new insight to a wide range of activities and actions.
  • The operation of the insight in real-time or near real-time [1]

Recent advancements in analytics and big data technology has widened the gap between what is possible and what is legally allowed. Organizations should be thoughtful in their use of Big Data; consulting widely and forming policies that record the decisions and conclusions they have come to.

Big Data touches those social, political, financial, and behavioral aspects of our lives with new considerations for the very way in which we understand and agree about the meaning of important words like identity, privacy, ownership, and reputation. The goal in Big Data is to develop a capacity to incorporate ethical inquiry into our normal course of doing business [2].

Organizations should consider the wider implications of their activities including: Context, Consent & Choice, Reasonable, Substantiated, Owned, Fair, Considered, Access, Accountable. These facets are called the ethical awareness framework. This framework was developed by the UK and Ireland Technical Consultancy Group (TCG) to help people to develop ethical policies for their use of analytics and big data [1].

References and Sources:

[1] Ethics for big data and analytics, Mandy Chessell (IBM)

[2] Ethics of Big Data, Kord Davis; Doug Patterson

Four exam questions and why are they good:

1. What are correlations in Big Data? This question makes the teacher know how well knows the student the topic. Correlations under my point of view is the base of Big Data, if there aren’t correlations there is not need to store and analyze the data, for that, it’s important the student has this concept clear.

2. What are Datafication and Digitization and their relation? With this question the student can explain the two terms separately and then explain why they appear related in the book, if they are different explain in what and if they are similar, what is the relation between them. Under my point of view, Datafication is a concept in Big Data that makes the distinction with the normal data and it’s important that the separation from digitization is clear.

3. What is the difference between Open Data and Big Data? In this answer the student can explain what is Open Data and the teacher can see if the student has both concepts clear. It’s a general question but very important since we have been speaking about the relation between both topics during the course.

4. If Open Data is free, how can anyone build a business on it? Since Open Data and the business around it is the main point of the book Open Data Now, it’s important to know where the beginning of a business could be with Open Data.

Coursera Diploma: veronicadiplomacoursera_criticalthinking_2015.pdf