Data Science has become the “sexiest job” of the 21st century. In an economy driven by data, businesses are hunting for talented data professionals who are skilled in transforming overwhelming amounts of data into actionable insights. Not surprisingly, many graduates are gearing their education towards a career in data science. Most universities do not offer major programmes in data science or degrees that are explicitly marked for data professionals.
Analytics is being used everywhere, in sectors from banking to medicine, sports, communication, media and even retail, whether online or offline. Industries such as sports, that you might not associate with big data are getting on-board, utilising analytics to improve performance and win more games.
With such a boom in the use of analytics, having the skills required to work with data isn’t just valuable – it’s a necessity. The importance of these skills is only going to become more important as more and more industries and businesses jump on to the bandwagon to remain competitive.
Data Science and Problem Solving
With the vast amounts of data from so many sources available and in real-time, a key skill for a data professional is to be able to put this data to good use and extract value from it in the form of insights that aid data-driven business decisions. The ability to think analytically and approach problems in the right way is a skill that’s essential, not just in the professional world, but in everyday life as well.
Beyond just the ability to extract valuable insights that aid in critical decisions, data professionals must be able to communicate effectively and articulate the insights that the data reflects to the concerned stakeholders, else the insights extracted as well as the source data – though a very valuable resource – would be wasted.
Data and its omnipresence
Data helps companies discover insights, new customers, and behaviours that can help businesses. This data is valuable to aid decision-making across functional areas such as Sales, Customer Experience, Marketing and Finance. Data can be exploited in these areas to extract key insights and move towards data-driven decision-making which can ultimately yield better organisational effectiveness.
Hence, while not everyone needs to be a data professional, there are a few key reasons why knowledge of data science helps, and especially if it is industry-specific:
- Being able to communicate with technical team members, knowing what to ask for and how it would help.
- Becoming data literate and understanding data science basics helps in becoming more independent in working with data.
- Clearly communicating your value proposition and why it is good, presented along with the insights and data to back it up, aids in getting approvals.
More about the breed
Data professionals have strong curiosity and passion for achieving practical business impact. They boast exceptional judgment combined with an analytical mindset. What sets apart the best from the rest is a knack for creative problem solving and a willingness to learn new technologies and skills.
Careers in data science commonly refer to the following roles:
- Data Engineers: Ensure data is captured from various sources & seamlessly integrated into their company’s ecosystem. Secure the quality of data & find methods for businesses to utilise the data. Leverage on data management tools to ensure that the ETL processes are automated & data marts created. Their goal is to optimise the performance of their company’s big data ecosystem.
- Data Analysts: Process data, run statistical analysis, create reports, summarise & visualise data. They are able to leverage on various data sources to derive actionable insights to solve problems. Work with business users to identify data that will be relevant in deriving insights. A data analyst must also have an understanding of the business goals & drivers.
- Data Scientists: Interdisciplinary practitioners who combine skills in computer science, mathematics, and business with a dash of curiosity. Identify both internal & external data required to solve a business problem while leveraging on advanced analytics to extract insights for an organisation. Translate the results of the analysis into business terms with required solutions/strategies. Work with both structured & unstructured data.
Preparing for a career in Data Science
There are various career paths in data science and two data professionals could come from different academic backgrounds, use different programming languages, and solve different problems.
While selecting your path and embarking on the journey towards becoming a data professional, it is important to take the following into consideration:
Willingness to Learn: Having a STEM background will help in your journey but it is not a necessity. You must be willing to learn the relevant skills, some of it may be easy to pick up while others will require considerable effort.
Take Relevant Courses: Data professionals need strong skills in maths, IT and computer science. There are a variety of subjects to master and you can opt for modules in the relevant undergraduate degrees.
Sharpen Communication Skills: Being able to interpret the insights extracted in business terms and effectively conveying this message in layman terms to the concerned stakeholders.
Most importantly, staying relevant is crucial to the ever-evolving field of data science. Given the current pace of constant technological innovation, continuing education is a hedge against shifts in the career market. Data science is a continuously evolving field, thus making a career-oriented data professional always keen to learn and evolve with the industry, and continuing to network and look for educational and professional development opportunities through training and conferences.
To get on the right path towards making a career in Data Science, drop us a line at firstname.lastname@example.org and we’d be delighted to work with you towards helping you achieve your goals. You may also visit https://mobiusgroup.co to explore what we have to offer.
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