2.5 Quintillion Bytes data is generated per day. Social media platform actually have a huge and critical contribution withinside the manufacturing of Big Data, in addition all of the tour businesses, hospitalities of the arena collectively produce many petabytes of statistics each day, although this data isn’t important to common person, however this statistics is of excellent significance to companies, new businesses and technical groups of public. Big organizations collect this Big Data from  various sources for their use, give information out of it and promote their business. Basically, production of Big Data comes from two sources: Machine and Humans.

Machine Made Data : This is the data which is generated by machines like computers and others, example computer logs and application logs.

Man Made Data : This data is produced by humans, we use different social platforms for sharing images, texts, video, voice mail, email etc through facebook, instagram, twitter, gmail etc. these all information are called data.

 HISTORY OF BIG DATA

The records of Big Data are very old, initially Big Data became utilized in 1663, this was the duration when Bubonic Plague unfold in Europe and John Gruant began doing research on it, on this connection John Graunt confronted a big quantity of information. At the time of 1880 it became visible as a huge problem to address Big Data, at that point the US Census Bureau introduced that it might take eight year to address and process the accumulated data. In 1881 someone from Hermann Hollerith Buero found a machine named “Hollerith Tabulating” invented .This gadget substantially simplified the task of census.

TYPES  BIG DATA

Data is infinite and data is found in many formats but for better understanding we can say that data is basically divided into three categories. Structured, Un-Structured, Semi-Structured.

STRUCTURED DATA

Any information that can be stored, accessed and processed in a fixed layout is known as Structured Data. Structured Data is appropriate to work with. Over time,In this contemporary world in which computer science has advanced new techniques for strolling with such information . Structured Data includes certain fields that suggest particular data, like names, phone numbers, spreadsheets which have columns and rows to keep information in a scientific manner for future access and uses. The records that are stored in RDBMS(relational database management system) are also structured data. Take a simple example of structured data, of mobile numbers and names recorded.

UN – STRUCTURED DATA

Un – Structured data is the data in which the information stored is not regular or There is no such preset format. It has many documents which are abnormal which have blended varieties of statistics like, textual content documents, motion pictures documents, snap shots documents, audio documents, facts of telecommunication, social media documents. So it turns out to be difficult to access this un- structured information and take more time to process this information. 

SEMI – STRUCTURED DATA Simply put, Semi – Structured data is the type of data that is neither fully structured nor unstructured,Semi-structured data lies someplace among the two. It isn’t always prepared in a complicated way that makes state-of-the-art access and evaluation possible; however, it could have information related to it, which includes metadata tagging, that permits factors contained to be addressed. 

Example:

A Word file is normally taken into consideration to be unstructured information. However, you may upload metadata tags withinside the shape of key phrases and different metadata that constitute the file content material and make it simpler for that file to be discovered while human beings look for the ones terms — the information is now semi-structured . Semi- Structured data isn’t in the shape of Relational Database however some of the organizational properties are there that facilitates in evaluation work and a few instances it may be saved in relational databases.