Historical Developments of Big Data

Last week in class we learned about how Big Data originated. It was first conceived by John  R. Mashey in the 90's, although the term is generally agreed to have been used first by Roger Mougalas in 2005. 

Despite this, ancient civilisations such as the Mayans used to record data using tally sticks. Other inventions such as the abacus made calculations easier. Early libraries emerged as a way to collect and store information. As time went on, the progression and development of Big Data grew exponentially. It surpassed an individuals ability to process information, and was even utilised in World War 2 to crack the enigma code used by the Axis! How cool is that?

The progression of Big Data is measured in phases. These include:

Phase 1.0 (1970-2000)

This is where data is collected in databases and data warehouses. It collected personal information and allowed summaries to be drawn between statistics. Early data mining started to take place although it took a couple of decades to reach its full potential.

Phase 2.0 (2000-2010)

This looked at websites and analysed clicks made by users on websites. This surge of data also meant that greater amounts of storage were required. This stage also introduced software such as Apache Hadoop. This 'data pool' stored large quantities of data that users could access. Social media and networking was starting to pick up which meant data was being produced faster than ever before, more and more storage space was required, it was growing exponentially.

Phase 3.0 (2010-Present)

This phase peaked when mobile devices became commonplace. People use their phones in everyday life, this allows researchers to track peoples hobbies and habits. This behaviour can be predicted, and businesses can use targeted adverts on consumers, based purely on their preferences. 

References:

https://ilearn.fife.ac.uk/course/view.php?id=9751#section-4