Data analytics (D&A) plays a crucial role in solving the toughest challenges in society, such as pandemic response, climate change, designing clinical trials, response to wildlife, predicting the needs of healthcare resources, making policy recommendations, and many more.
According to Nasscom, the demand for digital talent jobs in India is around eight times bigger than the size of its fresh talent pool—and it’s expected to be 20 times larger by 2024. The estimated open positions are at 620,000, but this could increase to 1.6M over the next four years.
Data continues to grow exponentially for businesses, too, and there is an ever more pressing need to turn this data into insights that can improve the customer experience. D&A platforms are keeping up with the evolving demand for data insights, resulting in new platforms, APIs, open-source tools, and algorithms to meet the needs and solve gaps faster.
To keep up, businesses will be seeking full-stack engineers who can create the data integration layer, standardize the data consumption layer, and enable prescriptive and descriptive reporting with embedded AI and ML models.
Likewise, they will need multi-skilled roles to handle the end-to-end data-to-insights journey. Businesses will need to reskill and upskill if they cannot fill the skill gap due to the supply and demand.
As analytics continues to be mainstream, the future of data and analytics careers seems brighter than ever. A modern data scientist should also carry data engineering and data storytelling skills to generate and communicate predictive and prescriptive insights to business stakeholders.
Tips on succeeding as a data analytics professional
Whether you are an aspiring data analytics professional or have been in this field for quite some time, you must continuously learn new skills to succeed. Here are some tips on setting yourself up for long-term success in this field:
Develop expert-level competencies
With business cycles becoming shorter, data and analytics have become all about speed, innovation, and continuous improvements in quality. Data science professionals need to think about how long it takes to recognize and understand the value they are generating for end-users. If it’s not clear or if it’s taking too long, they may be doing something wrong.
Data and analytics companies don’t just hire professionals to access specific tools. They are hiring for expert-level competency in cloud and data engineering, analytics and data management, business consulting, and service management. To succeed in this field, it’s important to develop a T-shaped profile at the minimum, though Pi-shaped is much better. It’s best to develop one or more competencies in the formative years, then diversify to build breadth across competencies for long-term success in your career.
Invest in learning essential technical skills
Data Modeling, Dimensional modeling and SQL are some of the basic skills a data analytics professional absolutely needs to have. But they are not enough. Go further and consider studying Java or R or Python for statistical programming. Python is one of the most common coding languages required in data science and data engineering roles, along with Perl, C/C++, or Java. A data analyst or engineer should also be capable of working with unstructured data.
Seek opportunities to learn predictive analytics, machine learning, and artificial intelligence to stay relevant. The key is to keep acquiring new skills and tools to stay up-to-date with the latest developments, technologies, and methods that will enable you to deliver the most effective solutions.
Develop your Data Storytelling Skills
As a data analytics professional, you should be good at data storytelling. The most important aspect of the data analyst’s job is communicating results from a technical perspective to non-technical audiences, such as the marketing or sales departments. To handle data appropriately, a data analyst must understand the demands of their non-technical team members and also empower them with quantified insights.
You need to be creative with data to help answer questions or solve problems. You must also apply the appropriate data visualization techniques to get your point across and enable your audience to understand the information easily. You also need presentation skills to keep your audience engaged.
Pursue continuing education
Having a Bachelor’s degree in computer science, sociology, physics, or statistics will provide you with the ability to handle and analyze massive data. However, you may need to pursue post-graduate education to advance your career.
According to KDnuggets, a leading industry resource on data analytics and machine learning, data scientists tend to be well-educated; 88% have at least a Master’s degree and 46% have doctorates. While there are outliers, most data scientists have a sound educational background that is necessary to cope with the demands of this profession.
If you plan to pursue post-graduate education, be sure to work in a company that supports this and will allow you to take classes after work or on weekends.
Do not forget your soft skills
Problem solving and collaboration are among the most important soft skills a data analyst needs.
Problem-solving is an essential aspect of data analysis. The bulk of analytics, about 90%, is focused on critical thinking. Thus it is vital to know what questions to ask. You will get the answers you need if the queries you ask are based on a firm’s knowledge of business, product, and industry.
A data analytics professional must also know how to collaborate with colleagues and clients. Careful listening skills are essential to understanding what type of data and analyses a client or stakeholder requires. The ability to communicate in a direct, easy-to-understand and clear manner also goes a long way in advancing your career. These soft skills can make you more effective at convincing people to act on the findings and help you resolve problems or conflicts.
Working at InfoCepts
If you are a driven, dedicated, and curious individual that is always ready to tackle data-driven problems, then a data analytics careeris a good fit. You must work in a company willing to support your professional and personal growth.
InfoCepts was recently named one of the best places to work for data scientists by Analytics India Magazine, alongside some of the biggest names in analytics. The company is known for nurturing a culture of development and investing in helping its associates become the best versions of themselves. If you are interested in pursuing a data analytics careerin a global company, explore the Careers section of the InfoCepts website.
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