In this tutorial we will discuss about the skills and steps for Data Scientist. More important thing is we will discuss in this tutorial is whether Scientist should be added or not. If yes why? We will go step by step in making of Data Scientist.
Data scientist looks cool when someone says that he is scientist in Data. There are two type of data scientist.
Now come to the point why they referred as Scientists which is not correct and we should not call them as Scientists. They should not be called as Scientist, who does not have PhD degree in the field of Mathematics.
So here we are clear that we should not call the as Data Scientist until and unless he does not have any PhD degree and published paper in that particular field.
We will use Data Scientist term for this tutorial
There’s nothing much different in Data Scientist and Data Analyst both needs almost same Skill set. One major difference is I am going to point out if you don’t like my difference please mention it in comments section.
Data scientists are rare unicorn and they masters whole range of Skill set. The unicorns who handle raw data and make them presentable to Data Analysts using different techniques like Python, R and so on…
Data scientists Role is Cleans the Data. Data may Unstructured. Unstructured means Data can be in any format.
Skills and talents for Data Scientist are Machine learning, Statistics, Modelling and techniques to visualizing data.
While on other hand Data Analysts are those who analyse and visualize the data using stats and math. And make it presentable.
Data Analysts role is Process clean data which is provided by Data scientist using statistical data analysis methods.
Skills and talents for Data Analysts are Excel spreadsheet, Database system(e.g. SQL MySQL), visulaization tools (e.g. Tableau, clickview, etc), and Stats.
