Analytics is the set of methods, techniques and processes used to collect, cleanse, interpret and transform data into actionable knowledge that supports operational and strategic decision-making. Its fundamental purpose is to extract insights from large volumes of structured and unstructured data to understand what is happening, why it is happening and what may happen next.
Analytics comprises several levels:
- descriptive analytics (what happened)
- diagnostic analytics (why it happened)
- predictive analytics (what could happen)
- prescriptive analytics (what should be done)
This layered approach enables organisations to progress from basic reporting to advanced decision-support and predictive modelling.
In practice, analytics relies on statistical techniques, data mining, mathematical modelling, machine learning, advanced visualisation and information systems that help organisations detect patterns, behaviours and emerging trends. It also involves processes such as data cleaning, feature engineering, automation of analytical workflows and the implementation of performance measurement systems.
Analytics is a central component of digital transformation and a core enabler of data-driven culture. It empowers organisations to enhance efficiency, innovate, reduce uncertainty and improve competitiveness. Its applications span marketing, finance, operations, supply chain, customer experience, human resources, cybersecurity, and sustainability.
According to some research institutions, companies that adopt advanced analytics achieve higher predictive capability, stronger operational agility and significantly improved decision quality. Analytics is therefore not just a technical function but a multidisciplinary approach that integrates data governance, human expertise, mathematical models and technology to convert information into measurable value.
