It will be better if you list-out students, their experience prior to join this course and their packages which you are placed as the course fee is 800000 but package is 600000 is too high for experienced people who has more than 5+ years so better come up with actuals rather concentrate on overestimation.
With a higher growth in the context of usage as well as data among each and every user in the corporate ecosystem. The analytics approach in order to calculate different metrics for an organization or big company is turning out to be a very humongous task, as the data set is getting bigger and bigger and replicating itself exponentially every moment. So due to this, the process to analyze the data and look out for a different and more effective technique to find the outcomes and insights of data set becomes a more difficult task. In short, with a wide increase in data due to more users and con
Both - Pricing as well Data are very good career options where numerical ability and analysing ability is of paramount importance and requirement.
It is upto you to think, analyse and decide which of them is good for you.
Data Sciences / Analysis is now in big demand and shall remain the future of Analytics.
Ideal path to become a Data Scientist is to first become a Data Analyst. For this, you can do BSc Maths / MSc Maths / BSc Statistics / MSc Statistics to begin with. Maths and Statistics is the base for data analysis.
Later as you gain experience, you can excel in the field and do a course in Business Intelligence, etc.
Business Analytics courses are also available after graduation however s a strong command over Maths and Statistics is inevitable.
Many analysts have dubbed "Data Scientist" as the sexiest job of the 21st century.
The expertise of skilled data scientists is becoming a hot commodity. Emerging from the need to analyze and utilize enormous amounts of data more effectively, companies are turning to data scientists to unlock the power of big data. Data scientists should have a broad-based understanding of business and data analytics capabilities and a working knowledge of related IT applications. In addition, they need strong communication skills to deliver their findings to all levels within an organization.