Best Alternative to a Data Science Course

In the October 2012 issue of Harvard Business Review, Data Scientist was named “The Sexiest Job of the 21^st Century.” Sexy or not, Data Science is definitely an interesting career choice. And it probably ranks high on your list of jobs you want to pursue. But, is it really something that will interest you in the long term? Or is there an alternative course to Data Science that’s far more interesting and lucrative?

The answer. There is, and it’s called Digital Business.

Now, we’ve discussed at length about how Digital Business is the future and the role it plays in Digital Transformation. However, many still grapple with the understanding of its applications and advantages. Digital Business is more than a job role, it’s a way of doing business. Data Science, on the other hand, is a job role. It’s an interesting field, yet falls short of all that Digital Business has to offer.

Before we inundate you on the pros of Digital Business, let’s see what Data Science involves and the paths your career can take with it.

What is Data Science?

Data Science is the mining and analysis of data for use by an organization. The data may be used for decision-making, strategy development, product development, customer journey analysis, forecasting, and much more.

A Data Scientist’s primary role is to research, extract, and present information that will be transformed into actionable plans.

Data Scientists work in a highly specific and strict environment as they deal with sensitive user and company data. They have to adhere to privacy laws and ensure user data is not misused in any way. Besides technical skills, Data Scientists should also possess excellent presentation and communication skills.

A Career in Data Science

Data Scientists deal with information day-in and day-out. They analyse massive bytes of data and extract information that can help the organization make decisions. However, Data Science is not all about statistics or analysis. Both form a part of a larger subject. Common skills that are required in Data Science include data mining, data warehousing, machine learning, statistical analysis, and big data analytics.

Small companies may not invest a lot in Data Science as their clientele is quite limited. Fortune 500 companies, though, – from Apple Inc. to Walmart to HP to Microsoft – use Data Science to study trends and manage growth. Data Scientists themselves are critical decision-makers in many companies as they are best-suited to analyse the path the company must take in order to grow.

Salary of a Data Scientist

Being a Data Scientist is surely a profitable endeavour. Salaries for Data Scientists can range approximately between INR 3,05,000 and INR 17,13,000 per year. On average, you can make about INR 6,75,000 as a Data Scientist. As you improve your skill-sets and experience, the salary too peaks. Experienced Data Scientists can make up to INR 27,00,000 per year.

Alternative Courses to Data Science

Forbes states, “there will be no data science job titles by 2029.” Notice they said “job titles” and not jobs. This means roles are evolving at a rapid pace. Companies are recognizing emerging trends and actively investing in them. Trends such as cloud computing, IoT, machine learning, etc. are on the rise and companies are looking for experts to fill these roles.

The best alternative to a Data Science course is Digital Business.

Why Digital Business Over Data Science?

When there is talk of a new job role in the market or when popular publications post articles saying “sexiest jobs”, everyone wants to be a part of it. Because that’s where the money is. That’s where employment is booming. No one wants to be left out. And many want to be the first.

Think of it as a mission to Mars. How cool would it be if you were the first person on the Red Planet? It’s the same with jobs. Wouldn’t you want to be the first of your role? That’s what Data Scientist was a few years ago. Everyone wanted to jump on the bandwagon and become one.

Up until there was a glut of Data Scientists and a lack of ROI. Data Science is still a lucrative job, but it is diluted by the sheer number of applicants.

What the Forbes article says is that Data Science jobs will evolve to become more complex. This doesn’t mean Data Science as a field of study should be ignored. It means that the course will come packaged in different forms. Different names.

Unlike Data Science, Digital Business is a multi-layered field. You have the option of choosing what you want to do, whenever you want to do it. The skills you imbibe as a Digital Business professional allows you to become an entrepreneur, an intrapreneur, or a digital business professional in any major organization. You are equipped with all the skills essential to succeed in a digital business environment.

Digital Business prepares you for job roles that are in demand today and those which will be created in the future.

In this fast-paced world, repetition becomes boring. The truth is every job has limits when it comes to job satisfaction. No matter how much developers love coding, they will ultimately get tired of looking at code over and over again. No matter how much Data Scientists love data, they’ll eventually tire of looking at it. Like life, your career too needs variety. With Data Science, it’s a linear line of growth.

With Digital Business, you have variety and more opportunities to make your career in a number of diverse and interesting fields.

Doesn’t that sound a lot better? You are not confined to a technical or managerial role. You have the option of pursuing both and equally succeeding at each. You will also be able to transition from one role to another with ease.

That’s why, at HETIC, the emphasis is on a student’s development in three key areas – technology, business and management, and design. Communication and interpersonal skills also form a significant part of the Digital Business course. When students graduate from HETIC, they are equipped with the right attitude and skills that will help them set up a career in any field of their choosing.