Generally we think of data scientists building algorithms,exploring data and doing predictive analysis. That's actually not what they spend most of their time doing however , we can see in the in the graph most of the time Data scientist are involved in data cleaning part , as in real world scenario we are mostly getting the data which is messey, we can feed the data after cleaning , ML model will not work if the data is messey, Data cleaning is very very important so mostly data analyst and data scientists are involved in this task. 60 percent: Cleaning and organising Data According to a study, which surveyed 16,000 data professionals across the world, the challenge of dirty data is the biggest roadblock for a data scientist. Often data scientists spend a considerable time formatting, cleaning, and sometimes sampling the data, which will consume a majority of their time.Hence, a data scientist, the need for you to ensure that you have access to clean and structured data can save y