Big Data

1. Definition

1.1. A term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis.

2. History

2.1. The term “big data” refers to data that is so large, fast or complex that it’s difficult or impossible to process using traditional methods.

2.2. The act of accessing and storing large amounts of information for analytics has been around a long time.

2.3. But the concept of big data gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the three V’s

2.3.1. Volume

2.3.1.1. Organizations collect data from a variety of sources.

2.3.2. Velocity

2.3.2.1. With the growth in the Internet of Things, data streams in to businesses at an unprecedented speed and must be handled in a timely manner.

2.3.3. Variety

2.3.3.1. Data comes in all types of formats.

3. Importance

3.1. Determining root causes of failures, issues and defects in near-real time.

3.2. Generating coupons at the point of sale based on the customer’s buying habits.

3.3. Recalculating entire risk portfolios in minutes.

3.4. Detecting fraudulent behavior before it affects your organization.

4. How it works

4.1. 1) Set a big data strategy

4.2. 2) Know the sources of big data

4.3. 3) Access, manage and store big data

4.4. 4) Analyze big data

4.5. 5) Make intelligent, data-driven decisions