All about PGDM Data Science

What is Data Science?

Data Science in its most basic terms can be defined as obtaining insights and information, really anything of value, out of data. The field is always tempting but counterproductive to try out put concrete bounds on its definition.

Data Science is basically a concept that unifies statistics, data analysis, machine learning, domain knowledge and related methods to understand and analyse actual phenomena of an event. Basically, data science is an interdisciplinary subject that focuses mainly on extraction of data from data sets which are typically large.

Few lines about PGDM Data Science

The PGDM Data Science is a 2-years postgraduate course that is divided into 4-semesters. The course offers a specialisation in capital markets, digital supply chain or healthcare. The course is offered in combination,  the strengths of a business and data science field.

The course will help the students to get on the management track by becoming a chief data officer or chief digital officer. The course gives a detailed understanding of data science and management and also explores the inter-disciplinary functionality between data science and management in real-world.

Eligibility for PGDM Data Science Course

The students interested to join PGDM Data Science course are required to possess the following eligibility criteria.

• The candidate should have passed Bachelor’s degree with at least 50% aggregate (or equivalent) from a recognized University 
• Qualification in any of the competitive management entrance examinations CAT/MAT/XAT/GMAT/CMAT/SNAP/NMAT/PGCET/KMAT is mandatory
• The students having more than one year of work experience is an added advantage

Admission Procedures

The students can take admission to PGDM (Data Science) by two modes. The first one is merit-based admission and second one is direct admission.

Merit Based Admission

The students interested in merit-based admission for PGDM (Data Science) courses are required to appear for entrance exams conducted at national and international levels. The students have to appear and qualify these entrance exams in order to get merit admission to the PGDM course.

Direct Admission

The students have another option of getting admission to PGDM (Data Science) course by direct admission process. Under this mode of admission, the students are given direct admission to their desired colleges and deemed or private universities under management quota. The direct admission students enjoy many special privileges like that they are not required to apply for any entrance exam for getting admissions. They have an option to choose their desired colleges and universities and book their seats in advance even before the starting of the academic year. The students who are interested in direct admissions are required to contact Galaxy Educational Services for more details.

Course Curriculum

The students of PGDM Data Science will be studying the following subjects during their course duration.

Career & Scope

There is a huge demand for PGDM Data Science students. They are hired in large numbers in various IT solution companies and financial institutions.

Salary & Emoluments

The fresh PGDM data science students will be earning around 5 lakhs to 9 lakhs per annum. The experienced professionals will be earning around 9 lakhs to 15 lakhs per annum.

Top Organisations hiring PGDM Data Science students

Some of the top organisations hiring PGDM data science students are:

• IBM
• Microsoft
• Google
• SAP
• Goldman Sachs
• JP Morgan Chase

Placement Opportunities

Some of the job roles available are:

Data Analyst: A data analyst’s primary job is to look at company or industry data and use it to answer business questions, then communicate those answers to other teams in the company to be acted upon. For example, a data analyst might be asked to look at sales data from a recent marketing campaign to assess its effectiveness and identify strengths and weaknesses. This would involve accessing the data, probably cleaning it, performing some statistical analysis to answer the relevant business questions and then visualizing and communicating the results.

Data Scientist: The data scientists do many of the same things as data analysts, but they also typically build machine learning models to make accurate predictions about the future based on past data. A data scientist often has more freedom to pursue their own ideas and experiment to find interesting patterns and trends in the data that management may not have thought about. As a data scientist, one might be asked to assess how a change in marketing strategy could affect your company’s bottom line. This would entail a lot of data analysis work (acquiring, cleaning and visualizing data), but it would also probably require building and training a machine learning model that can make reliable future predictions based on past data.

Quantitative Analyst: The Quantitative analysts, sometimes called “quants”, use advanced statistical analysis to answer questions and make predictions related to finance and risk. Needless to say, most data science programming skills are immensely useful for quantitative analysis and a solid knowledge of statistics is fundamental to the field. Understanding of machine learning models and how they can be applied to solve financial problems and predict markets is also increasingly common.

Data Warehouse Architect: This is a speciality or sub-field within data engineering for folks who’d like to be in charge of a company’s data storage systems. SQL skills are definitely going to be important for a role like this, although you’ll also need a solid command of other tech skills that’ll vary based on the employer’s tech stack. You won’t be hired as a data warehouse architect solely on your data science skills, but the SQL skills and data management knowledge you’ll have from learning data science make it a position that should be on your radar if you’re interested in the data engineering side of the business.

Business Intelligence Analyst:  The business intelligence analyst is essentially a data analyst who is focused on analysing market and business trends. This position sometimes requires familiarity with software-based data analysis tools (like Microsoft Power BI), but many data science skills are also crucial for business intelligence analyst positions and many of these positions will also require Python or R programming skills.

Marketing Analyst: The Marketing analysts look at sales and marketing data to assess and improve the effectiveness of marketing campaigns. In the digital age, these analysts have access to increasingly large amounts of data, particularly at companies that sell digital products and while there are a variety of software solutions like Google Analytics that can allow for decent analysis without programming skills, an applicant with data science and statistics chops is likely to have a leg up on many other applicants if they also have sufficient domain knowledge in the area of marketing. Plus, a marketing analyst whose analysis makes a significant impact can set their long-term sights on a Chief Marketing Officer position, which pays an average of $157,960 per year.

Operation Analyst: The Operations analysts are typically tasked with examining and streamlining a business’s internal operations. Specific duties and salaries can vary widely and not all operations analyst positions will make use of data skills, but in many cases, being able to clean, analyze and visualize data will be important in determining what company systems are working smoothly and what areas might need improvement.

Final Words

The PGDM Data Science students can find ample job opportunities in this field. PGDM Data Science is a new field and there is a lot of demand for skilled professionals. The PGDM Data Science students are paid handsome salaries and can expect excellent career growth in the field. The students who have an interest in data science and management can join this course.