Bigdata Analytics

Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large that it’s difficult to process using traditional database and software techniques.

While the term may seem to reference the volume of data, that isn’t always the case. The term big data — especially when used by vendors — may refer to the technology (which includes tools and processes) that an organization requires to handle the large amounts of data and storage facilities.

The term big data is believed to have originated with Web search companies who had to query very large distributed aggregations of loosely-structured data.

An Example of Big Data

An example of big data might be petabytes (1,024 terabytes) or exabytes(1,024 petabytes) of data consisting of billions to trillions of records of millions of people — all from different sources (e.g. Web, sales, customer contact center, social media, mobile data and so on). The data is typically loosely structured data that is often incomplete and inaccessible.
When dealing with larger datasets, organizations face difficulties in being able to create, manipulate, and manage big data. Big data is particularly a problem in business analytics because standard tools and procedures are not designed to search and analyze massive datasets.

Big data may also be called enterprise big data.