Trip into the history of data science.

Data Science has revolutionized several different aspects of our world. Let's take a look then at when and where data science comes from.

·         In 1962, John W. Tukey wrote in “The Future of Data Analysis” - The first milestone in the history of data science is globally recognized for the bright American mathematician John Tukey. The influence of John Tukey in statistical terms is enormous, but the most famous coinage attributed to him is related to computer science. In fact, it should be mentioned that he was the first to introduce the term "bit" as a contraction of "binary digit."

·         In 1974, Peter Naur published the Concise Survey of Computer Methods, which surveyed data processing methods across a wide variety of applications. The term “data science” becomes clearer, as he puts his own definition on it: “The science of dealing with data, once they have been established, while the relation of the data to what they represent is delegated to other fields and sciences.”

·         In 1977, the International Association for Statistical Computing (IASC) was founded.

·         In 1989, Gregory Piatetsky-Shapiro organized and chaired the first Knowledge Discovery in Databases (KDD) workshop.

·         In 1994, BusinessWeek published a cover story on “Database Marketing.”

·         In 1996, on the occasion of the conference of the International Federation of Classification Societies (IFCS), for the first time, the term “data science” is included in the title of the conference (“Data science, classification, and related methods”). In the same year, Usama Fayyad, Gregory Piatetsky-Shapiro, and Padhraic Smyth publish “From Data Mining to Knowledge Discovery in Databases.”

·         In 1997, during his inaugural lecture as the H. C. Carver Chair in Statistics at the University of Michigan, Jeff Wu called for statistics to be renamed “data science” and statisticians to be renamed “data scientists.”

 

 

Data Science: Most Blooming field in the 21st century.

    Our digital world creates a massive amount of data each and every second. Thanks to the communication devices, sensors and computations we use they capture information of great value to business and government across the globe. There is an explosion of data around us, and Data Science and Big Data are transforming our world and touching our daily lives like never before. It is believed that over 2.5 quintillion bytes (2.5 e+9 GB) Data is created every day and the number is increasing in order. 

Companies like Walmart, Adidas Entertainers like Spotify, Netflix Search engine companies such as Google, Yahoo! Leagues like NBA (National Basketball Association is a professional basketball league in North America.) USE has created an entirely new business model by capturing the information freely available on the web and providing it to people in useful ways. They collect trillions of bytes of data every day and continually add new services to their businesses to improve them.

Data science enables businesses to process huge amounts of structured and unstructured big data to detect patterns. This in turn allows companies to increase efficiencies, manage costs, identify new market opportunities, and boost their market advantage.

Asking a personal assistant like Alexa or Siri for a recommendation demands data science. So does operate a self-driving car, using a search engine that provides useful results, or talking to a chatbot for customer service. These are all real-life applications for data science.

• Will see some of the definitions from some famous websites.

1. Definition from IBM

Data science is a multidisciplinary approach to extracting actionable insights from the large and ever-increasing volumes of data collected and created by today’s organizations. Data science encompasses preparing data for analysis and processing, performing advanced data analysis and presenting the results to reveal patterns and enable stakeholders to draw informed conclusions.

 2. Definition from Edureka

Data Science is a blend of various tools, algorithms, and machine learning principles to discover hidden patterns from the raw data.

3. Definition from Wikipedia

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from many structural and unstructured data. 

4. Definition from DataRobot

Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights that analysts and business users can translate into tangible business value.

 5. Definition from ComputingForAll

Data science is a field of study that focuses on techniques and algorithms to extract knowledge from data. The area combines data mining and machine learning with data-specific domains.

6. Definition from Omni. sci

Data science enables businesses to process huge amounts of structured and unstructured big data to detect patterns. This, in turn, allows companies to increase efficiencies, manage costs, identify new market opportunities, and boost their market advantage.

• This is a simple video that will clearly describe data science.