Data Engineering Techniques for Cost-Efficient Retail Data Analytics

In the evolving landscape of retail, data-driven decision-making has become paramount for achieving competitive advantage and operational efficiency. This manuscript explores the various data engineering techniques that enhance cost efficiency in retail data analytics. By leveraging advanced technologies and methodologies, retailers can optimize their data management processes, ultimately driving business growth while minimizing costs. The study emphasizes the importance of effective data integration, transformation, and analysis, providing a comprehensive overview of the statistical methods employed in retail analytics. Additionally, a statistical analysis table illustrates the cost impacts of different data engineering techniques, demonstrating their effectiveness in improving retail outcomes. The findings reveal that implementing cost-efficient data engineering strategies significantly enhances retailers' ability to derive actionable insights, ultimately leading to increased profitability.