Data Science was not even a thing about 20 to 25 Years ago. Why? And why do we require data science now?
When the Computers came into existence, Data or information started to get recorded into excel sheets and insights were made manually and easily due to less amount of data, but as soon as Internet made its debut and connected people, commodities, cultures, businesses together huge amounts of data was generated and that was the point where a person dedicated to concluding insights from this data and help reinforce businesses along with proper decision making data Science need of the hour.
Data Science in simple words can be said to be a type of science which uses scientific techniques to gather valuable insights from raw data which proves to be beneficial for the businesses.
Eg: one has to predict the amount of revenue a food joint will generate if this food joint is opened in a hilly area , the data collected will be analysed which will include the geographic ,demographic and behavioural disposition of the population.
Data Science Being a science cannot be clubbed into one category, it involves all aspects from collecting raw data, to cleaning it, to organizing, analysing, predicting and creating insights.
The amount of data which we have today is huge hence “big data” requires scientific techniques which can decode this big data and juice the needful information into understandable insights for which one should have a good grip on computer languages like:
- Python
- SQL
Libraries like
- Pandas
- Matplotlib
Data visualization tools like:
- Tableu
- Hadoop
Machine Learning techniques like:
- Sklearn
Operating and control system like:
- Linux and Git.
A person who specializes in the field of data science is known as data scientist but how to become one?
Lets Map the career path for the same:
There are two paths:
- Management path
- Individual contributor path.
The individual contributor path includes data scientists who work on core projects, contribute code, run analyses, and build ETL pipelines and machine learning models.
The management path encompasses data scientists who manage people, scale data strategy, and work on fitting the pieces of a data organization together.
Paths:
- B.tech in Data Science
- BBA in Data Science
- BCA in Data Science
- BA/B.Sc in Mathematics/Statistics
- BA /B.Sc Economics Honors
- Learning Programming Languages
- Certification courses
In short data science can be pursued by anybody who has computer science, business expertise, maths or statistics in their pockets
About 11.6 million data science jobs will be generated by the year 2026
So Data science is the field which isn’t going anywhere anytime soon as the technology, business , education , healthcare , food and other industries relies on the data completely due to the market going global, virtual and data is the only thing keeping it together.
