Data analysts, engineers, and scientists, at a base level, make information easily accessible, digestible, and useful. They might design and build systems for collecting, storing, and deciphering data, or they might use existing or handmade tools to sort through data, identify patterns or problems, and make predictions.
Their work is essential for just about every industry you can think of, from retail to finance to tech. With access to and an understanding of data, companies can improve the customer experience, prevent cyberthreats, streamline processes and costs, and make smart decisions for the future of their businesses. As data becomes more vast and the talent pool struggles to keep up, data and analytics experts will continue to be in high demand. According to a 2020 global McKinsey survey, business leaders cited data analytics as the business area with the greatest need to address skills gaps.
If you’re ready to take your career to the next level in this field, here are three tips for upskilling in data and analytics.
Master hard skills with online and in-person training
Depending on your company’s needs, you likely use a programming language such as SQL or Python to analyze and visualize data. In other cases, Microsoft Excel or a business intelligence platform like Tableau or Zoho Analytics may be your tool of choice.
One of the best ways to keep these skills sharp is through continuing education, such as a certification, course, or bootcamp. Prestigious universities like Columbia Engineering and MIT offer classes for all levels, or you could sign up for a more immersive experience via a platform like Springboard or General Assembly. On Coursera, you can find more specific learning opportunities, such as an online course focused on Excel basics for data analysis, in partnership with major companies like IBM.
Keeping tabs on emerging tech like artificial intelligence is also important for data experts looking to stand out and stay ahead of the competition. Resources like AI News, Google AI, OpenAI, or MIT Technology Review can provide information on the latest updates, tools, research, and conferences.
Finally, practice your hard skills regularly so they remain fresh and applicable to all situations by taking on new assignments, or through side projects and open-source work on a platform like GitHub.
Build management or business administration expertise
Senior roles in data and analytics involve people and project management. If that’s your ultimate goal, it’s important to start building those skills now.
It may make sense to get an MBA or more specialized master’s degree. Or, you might consider a general management training, such as one offered by the American Society for Engineering Management.
Day to day, find ways to challenge yourself as a leader. This may mean raising your hand to run point on an upcoming project, coming up with a new system for a common workflow, or networking with managers you admire to learn how they got to where they are.
Hone your soft skills with hands-on experience
Succeeding in data and analytics — and becoming a respected leader in the field — requires strong soft skills, too.
Communication, critical thinking, problem solving, and more can be developed and honed through practice and exposure to unique challenges and situations. This requires constant collaboration and interaction with other experts in your field, and an openness and willingness to make mistakes, be uncomfortable, and ask questions. Reading about your field in blogs or publications, or following industry experts — CEOs or researchers in AI, data, or machine learning — on social media or Reddit communities like r/datascience and r/machinelearning can also help you stay up-to-date on the latest tech and trends.
The possibilities with data and analytics
Associate or mid-level data analysts and engineers can become directors, managing other engineers, experts, or workflows, or specialize in niches such as financial services or healthcare. As they move up, more opportunities arise to think creatively and innovate, and their work has the potential to really make an impact.
In the role of a chief data officer, for example, you’re not only tasked with managing an organization’s data strategy, but you might act as the face of the team and company’s vision in the media or at events; be a part of conversations around data ethics, compliance, or cybersecurity; and make key decisions around adopting or developing AI solutions. For these reasons, it’s only becoming more essential that data analysts and engineers have a strong grasp of emerging tech and trends.
Andela provides data solutions that improve decision-making and allow access to actionable insights from data, automate data workflows, and reduce risk by maintaining data compliance with industry regulations. Its solutions include services to design and construct robust data architectures and data migration on cloud platforms, assistance with statistical modeling and data mining, and real-time automation and predictive analytics.
Scale your data and analytics with Andela. Learn more.