Data science is a concept to integrate statistics, data analysis, machine learning and their related methods to process algorithms and systems to extract knowledge from structured and unstructured data.
The art of uncovering the insights and trends in data has been carried out by minds through the ages starting from ancient times. Egyptians were one of the first to precisely predict the flooding of the Nile river every year by collecting and analyzing data.
In 2012, Harvard business review marked ‘Data Scientist’ as the “The sexiest job of the 21st century.
There are many inter-disciplinary fields of Data science but in this section we can have categorized into its major components.
Data science enables us to find a solution for a direct or an indirect problem with the following generic steps:
Collecting data: After indentifying the problem in a data driven system, the first job is to have the required amount of data at hand and sometimes the data can also be recognized as Big Data.
Pre-processing data: Cleaning data means removing the discrepancies from the data such as missing fields, improper values, setting the right format of the data and structuring data from raw files.
Analyzing data driving insights and generating BI reports: Data analysis involves extracting, cleaning, transforming, modeling and visualization of data to uncover meaningful and useful information.
Taking decision based on insights: After uncovering a pattern in the data we can predict mathematical model by using machine learning so that we get into a state where we can decisions regarding the problem at hand.
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