Expecting to generate 800,000 jobs in artificial intelligence (AI) and big data analytics in just two years, the Telangana government announced 2020 as the State’s Year of AI. If government agencies themselves are seeing the growth of AI and data analytics, it must truly have arrived! But as an emerging field, it opens up a lot of — albeit loosely defined — careers for IT professionals. So, how to pick a career in data analytics?

We asked Springboard’s mentors for career advice on choosing the right data analytics path for professionals — both freshers and experienced. 

How to pick a career in data analytics?

  1. Gauge your interest

Data analytics is a vast field — encompassing everything from acquiring, wrangling and cleansing data to building business dashboards and predictive insights. You might find your interest anywhere in this spectrum. The best way to gauge your interest is to explore what data analytics entails, and perhaps even trying your hand at various aspects. 

Perform the following tasks and see how you like them.

  • With SQL or similar tools, write queries to extract the data you might need.
  • Use Pandas to perform data wrangling on any large open dataset you might find on Kaggle or KDNuggets etc.
  • Design databases for a specific purpose using tools like PgModeller.
  • Perform some purpose-led data analysis — like drawing supply/demand curves, identifying revenue trends, etc.
  • Try data visualization — can be anything from basic PowerPoint to advanced tools like PowerBI.

As you spend time working on each area, observe how confident and interested you feel. From there, explore roles that you might be interested in.

2. Identify the role you want

You have a wide range of options here. Based on your interest, see what role you might enjoy. Don’t just think about the present, also consider where this role will take you in the next 3, 5 and 10 years.

A data engineer builds the platform to capture and store data in an efficient and retrievable way. They’re interested in building data architectures and systems.

A business intelligence (BI) engineer develops, deploys, and maintains various BI tools and interfaces, as well as creates custom reports. They’re excited by identifying specific data points and reports from their data universe.

A data analyst finds patterns and draws insights from data, including trends and analysis of events that occurred. They can often be investigators, enthused by finding insight needles in the data haystack.

A database administrator is responsible for the performance, maintenance, and security of enterprise data. They are the folks who have the perseverance and keen eye for keeping the house in order. 

A data visualizer brings data to life through visualizations, graphs, maps, etc., to help business teams understand the information easily and accurately. They are both left and right-brained — have a creative flair with a clear understanding of data.

In various industries, these roles might manifest themselves differently. For instance, in an e-commerce company, your job could be to help the marketing team identify the best time to send out an email campaign. On the other hand, in a pharma company, you might even be helping scientists spot trends in clinical trials.

3. Match your skills 

Look beyond what the job description mentions as data analytics skills. Look within yourself — you might be an SQL expert or you know about everything there is to know about your industry. Go through the roles you’ve shortlisted, see what skills they seek, and map them to your skill sets.

For instance, if you’re indeed an SQL expert and you are interested in a data engineer role, you might already have an upper hand in data wrangling tasks. Make sure you match all your relevant skill sets to the job you aspire for while planning a career move. If you need to develop skills in specific areas, invest in them — read books, join online courses, compete in hackathons, etc.

4. Leverage your experience

Professionals looking for a career-shift often tend to think of their old experience as useless. Don’t ever make that mistake. Every experience can be valuable if you know how to leverage it. Say, you’ve spent 5 years as a banker and are now moving to data analytics — look for jobs in the financial services space, where your experience still holds weight. 

5. How to pick a career in data analytics: Find your place

Which country/city/town you live in sometimes has a disproportionate impact on what jobs are available to you. It doesn’t mean you can use it wisely. If you live in Bangalore, it’s a goldmine for IT startups — understand that and tweak your journey to leverage it. If you live in Mumbai, you might have more opportunities to work with banks and other financial institutions. Delhi might introduce you to more governance and policy wonks. Look around you and make the most of what your environment presents to you.

Once you know exactly what job you want, you can either move. Or, best case, even convince your employer to let you work remotely. Don’t discard any possibility without trying it.

Don’t be short-sighted

Remember that your career isn’t just about your current or next job. You have several decades ahead of you, so have a long-term vision for where you want to be. Because, if you aspire to become Chief Data Officer one day, you might want to take up generalist roles, which will help you have hands-on experience across all aspects of enterprise data management. But if you’re excited by data forensics, then develop deep expertise and skill sets in the area — who knows you might just become the Sherlock Holmes of banking fraud one day!

Data analytics and related fields are just entering their prime phases. We expect that over the next few years, data analytics will grow exponentially and evolve rapidly. To find success and stay successful: 

  • Explore your interests and re-evaluate them from time to time. 
  • Keep an eye out for emerging roles — even as you are reading this, data strategist roles are popping up in the market. 
  • Sharpen your skill sets, even while you’re in stable jobs; the only way to grow is to always stay relevant. 
  • Cumulate your experience — when you move from one role to the next, remember to take your learnings along. 
  • If you have the option to move, do so — the world is your oyster! 
  • Articulate and check back with your goals, make sure you’re travelling in the right direction.

Welcome to the world of data analytics: We can’t promise it’ll be easy, but it sure will be adventurous. To give yourself an advantage while building your data analytics career, and get specific career guidance, consider Springboard’s project-based mentor-led online learning programs.