{"id":480,"date":"2022-01-10T00:00:00","date_gmt":"2022-01-10T00:00:00","guid":{"rendered":"http:\/\/174.141.233.253\/~avion2022\/2022\/01\/10\/data-science\/"},"modified":"2024-02-20T06:48:06","modified_gmt":"2024-02-20T06:48:06","slug":"data-science","status":"publish","type":"post","link":"http:\/\/174.141.233.253\/~avion2022\/data-science\/","title":{"rendered":"Data Science"},"content":{"rendered":"

Data science is a multi-sectoral field focused on extracting knowledge from data sets and applying the knowledge in actionable insights from data to solve problems in a wide range of application domains in any industry. <\/p>\n

Data science collects all the available data and extracts valuable data from it, implementing that data to grow business. <\/p>\n

Big data is becoming a booming tool for businesses of all sizes. Data scientists (data scientist who creates programming code and combine it with statistical knowledge to develop insights from data.) are responsible for breaking down big data into usable information and creating software that helps organizations and companies determine optimal operations.<\/p>\n

It uses techniques and theories drawn from many fields within mathematics, computer science, information science, statistics, and domain knowledge.<\/p>\n

Techniques used in data science:<\/strong><\/p>\n

There is various type of technologies used in data science.
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