Data Analytics for Finance Professionals

What is Data Analytics?

Data Analytics refers to the techniques to analyze data to enhance productivity and business gain. Data is extracted from various sources and is cleaned and categorized to analyze different behavioural patterns.

Top Tools in Data Analytics

  1. R programming
  2. Python
  3. SAS 
  4. Microsoft Excel

Why Become a Data Scientist? 

1. Talent Gap of Skilled Candidates

Data is expected to grow 50 times by 2021. The ability to analyze this data is not increasing proportionally.

2. Add Value to the Business

Data being the most valuable asset to a company, used in every field of the business.

3.Huge job opportunities

The demand for data scientists is steadily going up and there’s a significant deficit on the supply side. There’re a huge number of unfilled job positions across the globe due to lack of the required skill sets

4. Data Science is Versatile

There are numerous applications of Data Science. It is used in health-care, banking, consultancy services, and e-commerce industries.

 

Why is Data Analytics important?

Data Analytics has a key role in improving your business. Here are 4 main factors which signify the need for Data Analytics:

 

1. Hidden Insights

Hidden insights from data are gathered and then analyzed with respect to businesses.

2. Reports

Reports are generated from the data and are passed on to the respective teams and individuals to deal with further actions for a high rise in business.

3. Market Analysis

Market Analysis can be performed to understand the strengths and weaknesses of competitors.

4. Business Requirement

Data analysis allows improving Business to customer requirements.

Who can do this Course?

PG - CA, CS, CMA
Graduates - BCom, BAF, BMS, MCom
Aspirants planning to enter Data Analytics from any background can do this course.

 Data Analytics for finance professionals

What skills you will learn at the end of the programme?

By the end of this Data Analyst Master’s Program, you will:

  

Course Outline

Duration - 25 hrs ( Live Instructor lead learning)
Fees -
Support -
No of Projects-

 

 



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