How Data Analytics Is Becoming Essential Across Every Industry

Businesses generate large amounts of data through sales, customer interactions, digital platforms, financial transactions, supply chains, and internal operations. The ability to understand this information has therefore become valuable across many industries.

This shift is also influencing hiring. According to IBEF, data analytics and science accounted for 26% of hiring demand reported in India during Q4 FY25, placing the field among the major areas of recruitment. (Source)

For students exploring data analytics careers, this means opportunities are no longer limited to technology companies. Analytics skills can be applied in sectors ranging from banking and healthcare to retail, manufacturing, marketing, and consulting.

Data analytics involves collecting, organising, examining, and interpreting data to identify useful patterns and insights.

A retail company, for example, may analyse purchasing behaviour to understand which products customers prefer. A bank may use data to study financial risks, while a healthcare organisation can analyse information to improve operational planning.

In each case, the purpose is similar: turn raw information into insights that can support better decisions.

This is why data skills are becoming relevant across both technical and non-technical functions.

Today, data-driven jobs can be found across multiple sectors.

Some common applications include:

• Banking and Finance: Risk analysis, fraud detection, customer insights, and financial forecasting.
• Healthcare: Patient-data analysis, hospital operations, research, and healthcare planning.
• Retail and E-commerce: Customer behaviour, demand forecasting, pricing, and inventory planning.
• Marketing: Campaign measurement, audience analysis, and customer segmentation.
• Manufacturing: Production monitoring, quality control, and supply-chain optimisation.
• Technology: Product analytics, software performance, AI, and machine learning.

The role of analytics may differ from one industry to another, but professionals generally need to understand data and communicate what it means for the organisation.

The two fields overlap, but their focus can be slightly different.

Data analytics generally involves examining information to identify trends, patterns, relationships, and useful insights.

Business analytics applies analytical methods specifically to business decisions. A business analyst may study sales performance, operational efficiency, customer behaviour, or market trends and use those findings to recommend actions.

In practice, many organisations require professionals who can combine both abilities. Technical analysis becomes more valuable when someone can also explain how the findings affect business decisions.

Students interested in analytics can explore several roles depending on their skills and qualifications.

Common career pathways include:

• Data Analyst
• Business Analyst
• Business Intelligence Analyst
• Data Scientist
• Marketing Analyst
• Operations Analyst
• Risk Analyst
• Data Engineer

Some roles are more technical, while others require a stronger understanding of business processes.

For example, data analysts may spend more time working with databases, spreadsheets, SQL, and visualisation tools. Business analysts may focus more on interpreting requirements, identifying problems, and communicating recommendations to different teams.

Students do not need to master every analytics tool at the beginning. Building strong fundamentals first can make advanced learning easier.

Useful skills include:

• Spreadsheets: Useful for organising, analysing, and presenting smaller datasets.
• SQL: Helps professionals retrieve and work with information stored in databases.
• Python or R: Programming languages commonly used for deeper data analysis and automation.
• Data Visualisation: Tools such as Power BI or Tableau can help convert complex information into understandable dashboards.
• Statistics: Basic statistical concepts help students interpret patterns accurately.
• Communication: Analysts need to explain findings clearly to people who may not have technical backgrounds.

NASSCOM's 2025 technology compensation study also noted that expectations from campus hires have increasingly shifted towards advanced data analytics, AI/ML, and DevOps capabilities. (Source)

Yes. Computer application programmes can provide useful foundations for students who want to enter analytics and related technology roles.

A Bachelor of Computer Applications in Goa can help students develop knowledge of programming, databases, computer systems, and software applications. These fundamentals can later support learning in areas such as analytics, data science, and artificial intelligence.

Students who want to develop deeper computing knowledge can consider a Master of Computer Applications in Goa. MCA programmes typically build on areas such as advanced databases, software development, programming, and computer science concepts.

Students can strengthen either pathway by working on analytics projects, learning SQL and visualisation tools, and practising with real datasets.

Parul University Goa offers BCA and MCA programmes through its Faculty of IT and Computer Science. Its current BCA offerings include a general programme as well as options connected with areas such as artificial intelligence and cybersecurity.

The university also offers MCA education, with coursework that includes areas such as software engineering, advanced database management systems, data structures, and programming.

Such foundations can help students build the technical knowledge needed before specialising further in analytics or related technology fields.

Students can begin with spreadsheets and basic statistics before progressing to SQL, visualisation tools, and programming.

They should also work on practical projects. Analysing sales data, building a dashboard, studying customer patterns, or creating a simple reporting project can help students understand how analytics works in real situations.

As more industries rely on information to guide decisions, professionals who can interpret data and connect it with business problems may find opportunities across a growing range of data analytics careers.