The data industry is projected to grow by leaps and bounds over the next decade. Massive amounts of data are being generated every day with a quintillion bytes being the safe estimate. Data professionals and statisticians are of paramount requirement in this fast-paced, data-driven world. They perform many tasks ranging from identification of data sources to analysis of data. Additionally, they find trends and patterns in the existing data at hand, however, the real set of duties would depend from organisation to organisation. Since data is relevant in almost every field now, the statistical requirements would also understandably change with the various sectors.
Candidates aspiring to step into this industry would be expected to have a fair knowledge about the statistical software in use, being proficient in one increases the job prospects manifold. It is nevertheless advisable that the potential employees narrow down the types of companies they wish to work for, say, for example, biostatistical organisations, and hone their skills accordingly.
The most popular programming software utilised for statistical analysis is STATA, SAS, R and Python.
In the words of StataCorp, Stata is “a complete, integrated statistical software package that provides everything you need for data analysis, data management, and graphics”. This software comes in handy while storing and managing large sets of data and is menu-driven. It is available for Windows, Mac and Linux systems. Stata is one of the leading econometric software packages sold in the market today. Such is its importance, that many universities have incorporated this in their coursework to make their students jobs ready. Over 1400 openings posted on Indeed put forward Stata as a precondition for selection. Facebook, Amazon and Mathematica are some of the many companies that require STATA as one of the qualifications for statistical and econometrics related positions.
Being an incredibly versatile programming language, Python is immensely popular. It is accessible for most people as it is easy to learn and write. Organisations ranging from Google to Spotify, all use Python in their development teams. Recently, Python has become synonymous with Data Science. In contrast to other programming languages, such as R, Python excels when it comes to scalability. It is also considerably faster than STATA and is equipped with numerous data science libraries. Python’s growing popularity has in part stemmed from its well-known community. Finding a solution to a challenging problem has never been easier because of its tight-knit community.
This is a command-driven software package that proves to be useful for statistical analysis as well as data visualization. SAS has been leading the commercial analytics space and provides great technical support. The software is quite expensive, making it beyond reach for many individuals. However, private organisations hold a very large market share of SAS. It is relevant in the corporate world to a large extent.
Educational Qualifications and Online Courses
Employers typically look for statistics, economics, maths, computer science or engineering students for data-related jobs with more preferences given to candidates with post-graduate degree holders. The key skills in demand include proficiency in statistical software, model building and deployment, data preparation, data mining and impeccable analytical skills. People looking to upskill themselves or diversify into a different career path to attain a higher pay bracket should give the data industry a shot. Coursera, Udemy, LinkedIn and various other platforms provide affordable courses in data science, programming and analytics for this purpose. A career in data is a rewarding one, and also ensures maximum job satisfaction. This is a highly recommended profession in today’s time.