Experts state that data science is among the professional fields expected to dominate the future employment landscape. At present, there is no shortage of job opportunities, with demand spread across roles such as data engineer, data scientist and data analyst in multiple industries.

The discipline of data science broadly revolves around five fundamental aspects. These include collecting data, filtering and separating relevant information, analysing the data, creating a model based on the analysis and finally visualising the results. Each step plays a critical role in transforming raw information into meaningful insights that support decision-making.

For instance, individuals searching to purchase a new house often share their preferences online, such as kitchen layout, living room design and overall space requirements. Gathering such information from different sources constitutes the first step. The second step involves separating essential details from the collected data, such as isolating only kitchen-related preferences from a larger pool of information.

The third step focuses on analysing the price of a house by comparing it with the prices of similar houses available in the dataset. The fourth step is building a predictive model that can estimate the price of a new house using patterns identified in existing data. The fifth and final step involves presenting the analysed information in a graphical or visual format, making it easier to understand and interpret.

Large volumes of such data are readily available on the internet. However, for organisations that operate in environments without internet access, specialised software programs are used to process and analyse data. Several widely used tools support data science activities, including R programming, Tableau, Microsoft BI, Google Charts, Python and SAS.

Experts point out that individuals with a strong interest in mathematics and statistics can learn data science with relative ease. In addition, those who have studied computer science, statistics, mathematics or engineering are considered well suited for this field. Mental aptitude for working with numbers, patterns and large datasets is also essential. Practical knowledge of Excel is often required, while familiarity with programming languages and analytical tools such as R, Tableau, Microsoft BI, Google Charts, Python and SAS is regarded as an added advantage for aspiring professionals.

Regarding education pathways, data science can be studied online through IIT Madras, where only a Class 12 qualification is required. The programme is offered at three levels—basic, diploma and degree—with the option to exit after completing a diploma. Examinations are conducted in person. Apart from this, several other IITs also offer data science courses, while many private institutions provide certificate programmes. Preference is generally given to candidates with backgrounds in statistics, computer science and mathematics.