Definition of Data Science

Before we discuss data science further, it doesn't hurt for us to get to know what data is. Data is a record of a collection of facts. these facts will be processed using data science and produce information.



after an information is obtained, the information can become data again and be processed again into new information, confused?



example: a company has sales data for the month of January, and this data will produce information on how much sales profit during the month of January. Then we can process the collected information again to obtain sales profit information for one year.



data itself can have many formats such as text, numbers, images, audio, etc.

Understanding what is Data Science

First, we must know what data science is. Data Science is a combination of various tools, algorithms and machine learning principles with the aim of discovering hidden patterns from raw data. then what makes it different from statistics in general?



The answer lies in the difference between explaining and predicting.



As you can see from the image above, a data analyst usually describes what happened with the data. On the other hand, Data Scientist not only performs exploratory analysis to find insights from it, but also uses various sophisticated machine learning algorithms to identify the occurrence of certain events in the future. A data Scientist will look at data from multiple angles, sometimes angles that were previously unknown.



Data Science is more often used to make decisions and predictions using predictive causal analysis, analytics (predictive and decision science) and machine learning.

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