Data Scientist- A key pillar for the growth of any Organization

“Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.” Geoffrey Moore


Whenever I hear the term “Data Science”, it always looks like a foreign language to me. So I started exploring about it. As I started learning, I found myself going deep insight another interesting world. There are things which look hard from outside but are actually very soft from inside. It’s up to your view to the stuff. Till the time we don’t find interest on the path, it always looks tough. But as soon we start working on it, the path turns out interesting. This interest serves as a motivation even on the toughest path ahead.


Data Science is no exception. Once you start exploring, you will find yourself enriched with deep knowledge and ready for new challenges at every step. Person working on the data science responsibilities is positioned as Data Scientist. This position is an important pillar in every field. Data Scientist can work in any domain like healthcare, IT, hospitality etc.


Importance of Data Scientists in Business:


- Business Intelligence for Smarter Decisions

- Making Better Product

- Managing Business Efficiently

- Predict Analysis to predict outcome

- Automating Processes

- Leveraging for Business Decision

As we live in the world of competitions, there are many companies working in the same field. For one problem, people can find n number of solutions by applying different approaches. But the one that comes out with fast and accurate result is always the wining company.

Data Scientist Responsibilities:


Data Scientists work like a stair for any organization. They are the persons who take company to the next level in very less time. Data Scientists work very close with contributors to understand how data can be used to achieve particular goals. They work on predictive models to extract data according to business need and help them to analyze data. They create algorithm’s, and design data modelling processes.


The process for analyzing and gathering data follow some methods:

- Acquire data

- Clean and Process the data

- Integrate and store data

- Data analysis

- Choose one or more potential models and algorithms

- Apply data science methods and techniques, such as machine learning, statistical modeling, and artificial intelligence etc.

- Measure and improve results

- Present final results to stakeholders

- Make adjustments based on feedback

I hope this has helped you get to know the importance of the Data Science as well as Data Scientist. We will work as a team in your learning path to Data Science. Stay tuned for my next blog.

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