Big Data Analysis Helps Organizations


Evolution of big data analytics

90% of the available data has been created in the last two years and the term Big Data has been around 2005, when it was launched by O’Reilly Media in 2005. However, the usage of Big Data and the need to understand all available data has been around much longer. In fact, the earliest records of using data to track and control businesses date back from 7.000 years ago when accounting was introduced in Mesopotamia in order to record the growth of crops and herds. Accounting principles continued to improve, and in 1663, John Graunt recorded and examined all information about mortality roles in London. He wanted to gain an understanding and build a warning system for the ongoing bubonic plague. In the first recorded record of statistical data analysis, he gathered his findings in the book Natural and Political Observations Made upon the Bills of Mortality, which provides great insights into the causes of death in the seventeenth century. Because of his work, Graunt can be considered the father of statistics. From there on, the accounting principles improved but nothing spectacular happened. Until in the 20th century the information age started. The earliest remembrance of modern data is from the 1887 when Herman Hollerith invented a computing machine that could read holes punched into paper cards in order to organize census data.


Why is big data analytics important for you

The Big Data analytics is indeed a revolution in the field of Information Technology. The use of Data analytics by the companies is enhancing every year. The primary focus of the companies is on customers. Hence the field is flourishing in Business to Consumer (B2C) applications.We divide the analytics into different types as per the nature of the environment. We have three divisions of Big Data analytics: Prescriptive Analytics, Predictive Analytics, and Descriptive Analytics. This field offers immense potential, and in this blog, we will discuss four perspectives to explain why big data analytics is so important today?

  • Data Science Perspective
  • Business Perspective
  • Real-time Usability Perspective
  • Job Market Perspective


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