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.

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