9 Facts About Data Science


Data Scientists and Data analysts are different  

Both are not the same. Data analysts try to find trends and information from the data. In contrast, Data Scientists work on finding trends and predicting new data from that data by making models. 


Data is not always clean 

In the real world, the data is not always purely clean. The data may be incomplete, inaccurate, duplicated, or inconsistent data. As Data Scientist you must be able to clean the data. 


The degree is not essential to become Data Scientist 

Everyone can learn and become a data scientist. You don’t need to have a specific Engineering or Ph.D. degree.   You need to have the skills required to become Data Scientist.  


Data Science Competitions and real-world projects are different 

Data Science Competition(like Kaggle) has limited data, evaluation rules, and no need to rewrite code after a certain time. But real-world projects are exactly the opposite of these. 


More Data does not mean more accuracy 

Adding more data may be required to reconstruct the model and also increases noise in the data sometimes. So more data may or may not improve the model’s performance. 


Data Science is not just one role 

Data Science does not mean only Data scientists. Data Science includes Data Scientists, Data Engineers, and Data analysts. 


Data science is not only for big organizations 

Data science has nothing to do with small or big organizations.  Data is everywhere, thus data science helps every organization. 


Communication skill for Data Science 

Communication skill is required to coordinate with team members as well as to present final results. thus this skill is necessary for Data Science. 


Focus on solving real-world problems 

Companies required a person who can solve real-world problems with Data Science. Therefore, make projects and showcase your skills. 


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