INTERVIEW QUESTIONS LATEST TECHNOLOGIES BIG DATA DETAILS

Question: What is Gartner's definition of the 3Vs for Big Data?

Answer: In a 2001 research report and related lectures, META Group (now Gartner) analyst Doug Laney defined data growth challenges and opportunities as being three-dimensional, i.e. increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources). Gartner, and now much of the industry, continue to use this "3Vs" model for describing big data.

In 2012, Gartner updated its definition as follows:-

"Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization."

Gartner's definition of the 3Vs is still widely used, and in agreement with a consensual definition that states that "Big Data represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value". Additionally, a new V "Veracity" is added by some organizations to describe it.

The 3Vs have been expanded to other complementary characteristics of big data:-

1. Volume: big data doesn't sample; it just observes and tracks what happens.

2. Velocity: big data is often available in real-time.

3. Variety: big data draws from text, images, audio, video; plus it completes missing pieces through data fusion.

4. Machine Learning: big data often doesn't ask why and simply detects patterns.

5. Digital footprint: big data is often a cost-free byproduct of digital interaction.

In a 2001 research report and related lectures, META Group (now Gartner) analyst Doug Laney defined data growth challenges and opportunities as being three-dimensional, i.e. increasing volume (amount of data), velocity (speed of data in and out), and variety (range of data types and sources). Gartner, and now much of the industry, continue to use this "3Vs" model for describing big data.

In 2012, Gartner updated its definition as follows:-

"Big data is high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization."

Gartner's definition of the 3Vs is still widely used, and in agreement with a consensual definition that states that "Big Data represents the Information assets characterized by such a High Volume, Velocity and Variety to require specific Technology and Analytical Methods for its transformation into Value". Additionally, a new V "Veracity" is added by some organizations to describe it.

The 3Vs have been expanded to other complementary characteristics of big data:-

1. Volume: big data doesn't sample; it just observes and tracks what happens.

2. Velocity: big data is often available in real-time.

3. Variety: big data draws from text, images, audio, video; plus it completes missing pieces through data fusion.

4. Machine Learning: big data often doesn't ask why and simply detects patterns.

5. Digital footprint: big data is often a cost-free byproduct of digital interaction. Source: CoolInterview.com

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