Introduction 

The field of information technology has been flourishing in the past decades. There has been exceptional growth in data and analytics. Technology is taking over the world with the introduction of new machines, smart machinery and much more. Artificial intelligence is making wonders leaving everything behind. If you’re wondering how data science took over our world, you have come to the right place. This blog will lay down the history of data science, how it started, and how is it one of the most spoken terms in today’s world. 

Each day more and more data introduces itself by various methods like shopping trends and behaviours. Businesses collect this data and store it in large amounts to make use of it in the future. Once this data began to expand big data came into existence. Businesses started using big data to solve data-driven problems and make various decisions. Big data started being used in the different fields of engineering, medicine and social sciences. 

  1. Background
  2. A brief history of data science

1) Background 

The history of data science dates back to early 1962 when John. W Turkey predicted the modern-day electronic computing effect. However, it wasn’t until 1964 when the first desktop Programma 101 was unveiled to the public. By 1981 IBM released its very first personal computer and Apple wasn’t far behind. Through the decade computer evolved at a fast pace. It took more two decades before the start of conversion of data into information and knowledge. 

In the 19th century, various academic philosophers began to discover the new discipline – data science. In 2005 a career in data science began to emerge when the National Science Board advocated for it. This was done to enable several experts who would successfully manage big data and digital data collection. 

2) A brief history of data science 

The history of data science can be summarised in six stages:

  • Stage 1

Contemplating the data power: It was in 1962 that John W Turkey published his famous article “The future of data analysis” in which he elaborated the relationship between data analysis and statistics. This stage endorsed the evolution of the data warehouse where the business transactions were centralised.

  • Stage 2

Further research relating to important data: As time progressed, the next period brought out the interests of various businessmen who started researching and collecting vast data. The International Association of Statistical Computing (IASC) was found in 1977. Turkey’s second article was also published during this time which stated the hypothesis for testing and data analysing. The period also witnessed the establishment of a workshop which was named Knowledge Discovery in Database which later came to be known as data mining.

  • Stage 3

Data Science gaining attention: This phase emphasises on the early market forms. Businesses started getting attracted to data science as it became more popular. The firms started to realise the importance and efficiency of data science. This led to a new era being born in the field of data science as businesses started implementing data science in their firm’s decision-making and earned huge profits. 

  • Stage 4 

Starting the practice of data science: The 20th century was the ultimate decade for the emerge of the field of data science. Data science started being recognised by various academic journals. Big data and data science became more popular and widely used for developing technology. William S Cleveland also contributed his talent towards this field. He co-edited the frameworks written by Turkey and developed significant statistical methods and also published a paper on data science.

  • Stage 5 

A new epoch of data science: This stage gave us the term data science, which was introduced by Jeff Hammerbacher and DJ Patil. The term wasn’t known by everyone yet but the idea it represented was being implemented by quite a few. According to research done by IBM, the statistics showed that up to 90 per cent of the total data available to the world was produced in the past two years. 

  • Stage 6

Data science in demand: This stage was the most prosperous time for the emergence of data science. Several companies started benefitting from data science and began to collect all kinds of data from different sources. The corporate firms experienced a major hike in demand for their products after implementing data science. Apple gave credit to big data and data mining for its increase in sales. Microsoft and Google started using voice recognition and speech detection technologies.

Conclusion 

To sum up, data science did not receive a very warm and popular welcome. Though it was often ignored by the researchers the field has come a long way about today’s world. It helped the firms gain huge profits, function effectively and improve their businesses. Data science helps in every field be it biological sciences, medical informatics, health care, or finance, government and economics. Data science has been proven useful and is advised to be implemented more and more. After going through the above blog, we hope you have understood what data science is, history of data mining and when did data science begin.

If you are interested in making a career in the Data Science domain, our 11-month in-person Postgraduate Certificate Diploma in Data Science course can help you immensely in becoming a successful Data Science professional. 

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