Paper Contents
Abstract
In the age of data, organizations increasingly depend on data analysts to maximize operating efficiency and guide decision-making. This study examines the pivotal role of data analysts in converting raw data into useful business intelligence, in an e-commerce setup where real-time analytics were incorporated to maximize business performance. The study describes fundamental processes such as data cleaning, preprocessing, visualization, and predictive analytics, employing methods such as missing value handling, duplicate removal, and data normalization to enhance data quality. Various analyses were conducted to ascertain customer behaviour patterns, trends in sales, geographic performance, and payment issues. Predictive models were also used to predict product demand and store revenue, enabling businesses to make strategic planning decisions. Another significant contribution of this study is the combination of Google Analytics with an e-commerce database, enabling real-time monitoring of transactions, customer interactions, and sales trends. Furthermore, an interactive dashboard was created using Power BI to enable efficient presentation of findings and aid decision-making. The outcomes confirm that the use of data analytics, combined with real-time monitoring, considerably eradicates inefficiencies, improves customer retention, and provides businesses with the agility to respond to changes in market conditions, driving growth and competitiveness.
Copyright
Copyright © 2025 Het Thakkar. This is an open access article distributed under the Creative Commons Attribution License.
