The growing availability of digital data has changed the way businesses approach decision-making. Data generated through customer transactions, sales, financial activities, and business operations provides valuable information, but its usefulness depends on how effectively it is analysed and interpreted. This study examines the role of data analytics in transforming business data into meaningful insights that support informed decision-making.

The research focuses on the four major types of data analytics: descriptive, diagnostic, predictive, and prescriptive analytics, and their relevance to different stages of the decision-making process. It explores the application of data analytics in areas such as marketing, sales, finance, operations, customer management, and risk management. The study also considers how data-driven insights can help businesses identify trends, understand customer behaviour, forecast demand, improve resource allocation, and reduce business risks.

The research is based on secondary data, including relevant research literature, reports, and real-world business examples. Along with the benefits of analytics, challenges related to data quality, privacy, security, implementation costs, and availability of skilled professionals are considered.

The study provides an understanding of how data analytics can strengthen business decision-making and contribute to improved organisational performance.