ROLE OF MACHINE LEARNING AND ANALYTICS ON DATA-DRIVEN DECISION MAKING AND PROFITABILITY IN THE RETAIL GOODS SECTOR
DOI:
https://doi.org/10.53273/k46aq419Abstract
Information analysis is now a critical component in every practitioner and researcher's evaluation, as it reflects the impact and magnitude of the data-related problems being addressed by organizations such as list businesses. The study identified four key factors: information source, data evaluation equipment, protection of economic and financial outcomes and data, and security. It was designed to evaluate the influence that Big Data has on list businesses. The study examines how big data can affect list businesses that make data-driven decisions using information analytics and other business intelligence. This study has concluded that list companies' business analytics tools have a significant impact on the economy and finances. Information was collected for analysis by conducting a survey on various business practices, and the investments made in IT technology by companies listed. Information analysis showed that data-driven decision (DDD) organizations have higher outputs and productivity. The relationship between DDD, inventory usage, consumer engagement and the market value of the list business can be clearly seen using Smart PLS techniques and excellent evaluation guidelines.
Keywords: Data Source, Data Analysis Tools, Data Security, Economic and Financial Outcomes, FMCG Industry
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