Big Data

Big Data is a term that specifies the large, hard-to-manage volumes of data with more velocity. Big Data sets can't be processed in the traditional database management systems and tools. It encompasses the Volume of information, the Velocity or speed at which it is created and collected, Veracity refers to the uncertainty of available data, Value refers to turning data into value. and the Variety or scope of the data points being covered (known as the "five v's" of big data). Big Data often comes from data mining and arrives in multiple formats.

1. Big data is a great quantity of diverse information that arrives in increasing volumes and with ever-higher velocity.
2. Big data can be structured (often numeric, easily formatted and stored) or unstructured (more free-form, less quantifiable).
3. Nearly every department in a company can utilize findings from big data analysis, but handling its clutter and noise can pose problems.
4. Big data can be collected from publicly shared comments on social networks and websites, voluntarily gathered from personal electronics and apps, through questionnaires, product purchases, and electronic check-ins.
5. Big data is most often stored in computer databases and is analyzed using software specifically designed to handle large, complex data sets.

Types of Big Data

There are three types of Big Data

1. Structured Data: This is organized data which are in Database, excel sheets, datasets etc. It is easy to handle via the Business Analytics BI tools to read this data.
2. Unstructured Data: Unstructured Data are stored with no predefined conceptual definitions and is not easily interpreted or analyzed by standard databases or data models. Organizing unstructured data into structured data is time-consuming, but possible with the right solution. 
3. Semi-Structured Data: Semi-structured data is a combination of structured and unstructured data.