Data-Driven Decision Making for E-Business Success: A Review

Abstract

The revolutionary impact of big data in data-driven decision making (DDDM) is examined in this paper, with particular attention to its vital uses in e-business. According to the report, companies may use Big Data analytics to extract useful information from large, complicated datasets, which will ultimately lead to improved consumer engagement, tailored experiences, and operational efficiency. Artificial intelligence (AI), machine learning, and predictive analytics are examples of advanced technologies that are essential for spotting market trends, boosting innovation, and optimizing marketing strategies. Dynamic pricing, fraud detection, inventory management, and real-time campaign optimization are some of the primary uses that are highlighted. Businesses can stay flexible, competitive, and customer-focused in the digital economy with the help of these data-driven strategies. Big Data integration challenges are also covered in this assessment, including the need for strong data governance frameworks, ethical issues, and data privacy concerns. Expert staff and cutting-edge infrastructure are emphasized in the discussion of striking a balance between using innovation and guaranteeing accountability. Additionally, the research delves into the function of big data in promoting sustainability, emphasizing how its tactical use might stimulate social and environmental responsibility in global commerce. In order to help e-businesses go from intuition-driven to evidence-based decision-making, the results highlight how essential big data is. Organizations may open up new avenues for growth and innovation in a world that is becoming more and more data-centric by coordinating technology, strategy, and ethics.