Gone are the days when job candidates rushed to offices grasping paper cut-outs of vacancy advertisements. At present employers are keeping an eye out for people who can take their firms and their own careers forward. And a career in data analysis is one of the on-demand career prospects. Data analysts serve as data translators for those in the organisation who are not sure what inferences to make from their datasets.
Why choose a career in data analytics?: According to the World Economic Forum's (WEF) 'Future of Jobs Report, 2020' data analysts are estimated to be in great demand by 2025. A data analyst's career may be appealing for a variety of reasons, including a high median salary in a fast-growing sector. With a good mix of technical and communication work, plenty of great learning resources with room for career advancement, and a wide variety of roles, the field of data analysis is lucrative indeed. As firms seek data-literate experts to convert their raw datasets into smart insights and make data-driven decisions, career opportunities in data analytics are only growing better.
Career options for a data analyst: There are different routes to explore within the field of data analytics depending on several aspects, such as business analyst, data visualisation specialist, data scientist, data journalist, financial analyst, functional analyst, and so on. Among them, business analysts, data visualisation specialists, data scientists, functional analysts, project managers, and quantitative analysts are the highest-paying data analytics jobs with an average salary range of $82,343 to $178,606, according to payscale.com.
Required skills and qualifications: Employers in the field of data analytics care more about skills than specific degrees or certifications. So far, a bachelor's degree in a technical or non-technical discipline is necessary for any data analyst position. Then, having a solid understanding of any basic programming languages such as R, Python, SQL (Structured Query Language), etc. will give the proficiency to work with big databases. Besides, data manipulation, analysis, and visualisation skill-sets are crucial to understand and visualise the data and lastly, explain the outcomes from the dataset. Also, advanced abilities in software such as Microsoft Excel, Tableau and cognitive abilities like problem-solving, critical thinking, as well as their fluency in the programming languages must be in the knowledge domain of a data analyst.
What a teacher says: Assistant Professor of Economics at Shahjalal University of Science and Technology (SUST), Dr Munshi Naser Ibne Afzal often talks about diverse skills that matter for students' careers on his YouTube Channel, "Dr. Munshi Naser - Skill Tone."
In one of his lectures he discussed the top two freely available data visualisation tools for beginners, saying, "Without knowing any programming language, you can start with 'Tableau Public' and 'Power Bi' for your data analyst career."
Merely taking different courses is not recommended by him, as these will not enhance skills unless one uses the learning outcomes. He further advised that people begin the journey of data analysis using R and then switch to Python.
"Make friends with the Kaggle platform, which has over 6,000 datasets and allows aspiring data analysts to upload projects, create notebooks, and experiment with data in a very fundamental way," he added.
Views of two graduates: Susmita Dutta Prita, who completed her master's of Social Science in Economics with distinction at SUST, is currently working as a research associate at Economic Research Group (ERG). Since data analysis is an indispensable part of her research works, she opined, "Students from any background may become data analysts provided they master some particular skills like the capacity to utilise various software and models specified by the respective companies".
From her viewpoint, data analysis methods for various topics are multiplexed, so it may not be appropriate to simplify what skills are required to be a data analyst. She advised prioritising learning about data management, analysis method, and relevant tools before anything else.
"If you work on some projects little by a little while at university, you will be chalked up towards being a data analyst."
Farhin Islam did master's in Economics at the University of Dhaka and a research assistant at the South Asian Network on Economic Modelling (SANEM). She won a national data analysis competition and has sound expertise in MS Excel and Stata for data analysis.
According to her, data analysts explore meaningful information from meaningless values and data tools can be broadly categorised into three types: Data collection, data cleaning and analysis, and data visualisation," she said, "To stand out from the crowd, one must gather knowledge about all these types and should know at least one tool from each type".
She mentioned widely used tools such as Google Form, KoBo Toolbox, ODK for data collection; Excel, SPSS, Stata, Eviews for data analysis; Tableau and Power BI for data visualisation. "All tools have some benefits and drawbacks, so individuals may determine which one is suited for specific needs," she continued.
Core competencies for a data analyst comprise statistical expertise, critical thinking knack, and problem-solving abilities. Learning to deploy a tool is always a second priority to her, the first is perceiving how to think about a problem to solve it. "If the theoretical knowledge isn't robust enough, the application of those tools will surely be able to generate results, but the outcomes may be erroneous," she warns.
Life is nothing but moving forward to higher objectives, and there is no one-size-fits-all approach. There is every chance to accomplish more combinations of advanced skills. So, all the things' data analysts need are a specific passion, skill-sets, consistent working with data sources, and building a professional portfolio.
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