What is Big Data?
In short such data is so large and complex that none of the traditional data management tools are able to store it or process it efficiently.
The major problems faced by Big Data majorly falls under three Vs. They are volume, velocity, and variety.
- Volume: The data is getting generated in order of Tera to petabytes. The largest contributor of data is social media. For instance, Facebook generates 500 TB of data every day. Twitter generates 8TB of data daily.
- Velocity: Every enterprise has its own requirement of the time frame within which they have process data.Many use cases like credit card fraud detection have only a few seconds to process the data in real-time and detect fraud. Hence there is a need of framework which is capable of high-speed data computations.
- Variety: Also the data from various sources have varied formats like text, XML, images, audio, video, etc. Hence the Big Data technology should have the capability of performing analytics on a variety of data.
Types Of Big Data
Big Data could be found in three forms:-
Any data that can be stored, accessed and processed in the form of fixed format is termed as a ‘structured’ data. Over the period of time, talent in computer science has achieved greater success in developing techniques for working with such kind of data (where the format is well known in advance) and also deriving value out of it. However, nowadays, we are foreseeing issues when a size of such data grows to a huge extent, typical sizes are being in the rage of multiple zeta bytes.
Any data with unknown form or the structure is classified as unstructured data. In addition to the size being huge, un-structured data poses multiple challenges in terms of its processing for deriving value out of it. A typical example of unstructured data is a heterogeneous data source containing a combination of simple text files, images, videos etc.
Now day organizations have wealth of data available with them but unfortunately, they don’t know how to derive value out of it since this data is in its raw form or unstructured format.
Semi-structured data can contain both the forms of data. We can see semi-structured data as a structured in form but it is actually not defined with e.g. a table definition in relational DBMS. Example of semi-structured data is a data represented in an XML file.
Benefits of Big Data
1) Using the information kept in the social network like Facebook, the marketing agencies are learning about the response for their campaigns, promotions, and other advertising
2) Using the information in the social media like preferences and product perception of their consumers, product companies and retail organizations are planning their
3) Using the data regarding the previous medical history of patients, hospitals are
providing better and quick service.
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)