review · Computer Science & IT Research Journal
Modern organisations increasingly rely on business intelligence to extract valuable insights from large volumes of data. A wide range of analytical tools, spanning traditional querying and reporting to machine learning and predictive modelling, enables the transformation of raw information into actionable knowledge. Integrating business intelligence with big data analytics allows enterprises to monitor market trends, understand consumer behaviour, and improve operational efficiency. These capabilities support timely, evidence-based strategic decisions that improve overall agility and competitiveness. However, implementing these systems presents notable operational hurdles, particularly concerning data quality, system security, and shortages of skilled staff. Addressing these barriers requires organisations to establish robust data governance frameworks alongside ongoing investment in professional talent development to ensure sustainable analytical performance.
Organisations across all sectors generate vast quantities of digital information every day. Understanding how to deploy business intelligence and analytical tools effectively helps managers make faster, better-informed choices, improve productivity, and adapt to changing market conditions. It also clarifies the practical governance and staffing investments required to turn raw digital records into lasting commercial value.
Because this work is a broad literature review rather than a technical report on a specific tool or prototype, it does not present a direct commercial product. Instead, it provides strategic guidance for commercial enterprises and corporate decision-makers seeking to adopt existing analytical tools and governance practices to improve operational agility and competitive advantage.
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In the contemporary business landscape, the proliferation of Big Data has revolutionized the way organizations gather, process, and utilize information for strategic decision-making. This paper provides a comprehensive overview of the evolving role of Business Intelligence (BI) in harnessing the potential of Big Data and the subsequent impact on gaining a competitive advantage. The review delves into the arsenal of analytical tools that have emerged to handle the vast volumes of data generated in the digital age. From traditional reporting and querying to advanced analytics, machine learning, and predictive modeling, organizations now have a myriad of options to extract valuable insights from their data reservoirs. This paper investigates the efficiency, scalability, and adaptability of these tools in the context of Big Data, emphasizing their role in transforming raw data into actionable intelligence. Furthermore, the paper explores how the integration of BI and Big Data analytics contributes to the development of a competitive edge for businesses. The ability to harness insights from diverse data sources provides organizations with a holistic view of market trends, consumer behavior, and operational efficiency. This, in turn, empowers decision-makers to make informed and timely choices, enhancing overall organizational agility and responsiveness to market dynamics. The study also highlights the challenges associated with implementing BI in the era of Big Data, including issues related to data quality, security, and the need for skilled professionals. Effective solutions to these challenges are discussed, emphasizing the importance of a robust data governance framework and continuous investment in talent development. This paper underscores the pivotal role of Business Intelligence in leveraging the potential of Big Data for gaining a competitive advantage. As organizations navigate the complexities of the modern business landscape, the judicious use of analytical tools and the integration of BI with Big Data analytics stand as key drivers for informed decision-making and sustainable success. Keywords: Business Intelligence, Big Data, Analytical Tool, Business, AI, Review.
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DOI: 10.51594/csitrj.v5i2.791
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