A lot of people are confused about these terms. Article below will explain you in details and clear your confusion about these 2 topics.
So let’s get going on this discussion… Some companies don’t differentiate between a data scientist and analytics professional and use these terms interchangeably to define their team members. On the other hand, significant number of companies do have this differentiation. In general, here are the factors that in my opinion can separate the two-
However for being successful either as a Data Scientist or Business Analytics professional, following are the must have skills-
- Love for numbers and quantitative stuff
- Grit to keep on learning
- Love for coding and programming
- Structured thinking approach
- Passion for solving problems
- Good knowledge of statistical concepts
Here are my Top 10 Pointers to ensure durable success in either field–
- Learn as much as possible. Spend 4 to 5 hours every week on the learning and development and knowing the latest in the industry
- Challenge status quo. Never assume that whatever is being done is following the most effective approach
- Believe that you are equal to everybody else in the hierarchy. Don’t be afraid to speak your mind
- Focus on Innovation and coming out with the earth shattering ideas rather than doing the business as usual.
- Focus on developing great communication skills and soft skill as this is one of the biggest gap I have seen in the analytics professionals
- Don’t become a one trick pony. try to get exposure in different industries and different functional areas.
- Participate in competitions and events such as Kaggle, to know where you stand vis a vis your peer group.
- Try to write white papers and blogs on your subject matter expertise.
- Develop domain expertise as without that analytics is not effective.
- Finally, always maintain a clear visibility of your strength and opportunities and any blind spots. Actively seek feedback from your peer group and your superiors.
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