Data and analytics has become the bedrock of business strategies helping companies understand their customers, build better products, save costs, provide higher-quality services and transform their businesses. With the explosion in user-generated data and businesses wanting to deliver the right products at the right time, the data analytics industry has exploded as a career path. Job roles such as data engineers, analytics cloud professionals, data scientists, AI and machine learning engineers are in high demand today.
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 skills such as big data, analytics, cloud computing, mobility, machine learning and cyber security are in great demand.
To keep up, businesses will seek full-stack engineers who will be able to create the data integration layer, standardize the data consumption layer, and enable prescriptive and descriptive reporting with embedded AI and ML models. They will also need multi-skilled roles to handle the end-to-end data-to-insights journey. Due to the demand-supply gap, businesses will need to constantly reskill and upskill in addition to hiring experienced talent from the market.
Tips to succeed as a data analytics professional
With business cycles becoming shorter, data and analytics have become all about speed, innovation, and delivering business value. You need to think about how long it takes for end users to unleash value from the reports or insights you are generating. If it’s not clear or if it’s taking too long, you may be doing something wrong.
Whether you are an aspiring data analytics professional or have been in this field for quite some time, you have the opportunity to not only learn new skills, but also help shape the future.
Here are some tips to guide your long-term success in this area:
Develop expert-level competencies
Data and analytics companies don’t just hire professionals to access specific tools. Any end-to-end D&A projects now typically leverages upto eight technologies and companies are not willing to invest in multiple tool experts anymore. When it comes to cloud, companies use an average of 20+ cloud services and many customers are already using a multi-cloud setup. Building expertise in one or two tools is not going to take you far and building expertise in all is not going to be practical as new services are added every day.
Today, companies are hiring for experts in competencies such as cloud, data engineering, analytics, data management, advisory and service management. These competency experts are individuals who are able to work on multiple technologies in a competency and have the capability to create an end-to-end solution to a real-life data problem.
You should develop a T-shaped or Pi-shaped profile with depth in one (or more) competency in formative years and 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 learning Java, R, or Python programming. Python is among the most common coding languages required in data science and data engineering roles, along with Java.
A data analyst or engineer should be capable of working with unstructured data as well. Seek opportunities to develop your skills on 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 a data analyst’s job is communicating insights effectively to non-technical audiences, such as the marketing or sales departments. You need to be creative with data to help answer questions or solve problems. You must apply the appropriate data visualization techniques to get your point across and enable your audience to understand the information easily. Whether you are data engineer, data analyst or data scientist, you should develop your ability to present insights in the form of intuitive, information-rich dashboards.
Pursue continuing education
Having a bachelor’s degree in computer science, information technology, or statistics will provide you with the ability to handle and analyze 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. A management degree can also come in handy to help you reach leadership positions faster and excel in it. 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.
Focus on your problem-solving and soft skills
Problem solving and collaboration are among the most important soft skills a data analytics professional needs. Problem-solving is an essential aspect of data analysis – it is vital to know what questions to ask. You will get the answers you need if the queries you ask are based on your knowledge of the firm’s 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. In addition, these soft skills can make you more effective at convincing people to act on the findings and help you resolve problems or conflicts.
Data and Analytics Careers at Infocepts
Infocepts was recently named as Great Place to Work and as one of the best firms for data scientists to work for by Analytics India Magazine, alongside some of the biggest names in analytics. We exclusively focus on data and analytics and are known for investing in helping our associates become the best versions of themselves.