Ayodele Olagunju

Papers

Total Citations

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About

Ayodele Olagunju is a researcher whose work sits at the critical intersection of data engineering, business intelligence, and big data analytics. His primary research focus is on optimizing the Extract, Transform, Load (ETL) pipeline—the backbone of modern data warehousing—to handle the scale and complexity of big data environments. His most cited work, a systematic literature review of 97 papers, provides a comprehensive taxonomy and evaluation of current ETL implementation approaches, offering a vital roadmap for practitioners and researchers alike. This foundational study, with 12 citations, has become a key reference for those seeking to bridge traditional data integration with emerging big data technologies. Beyond this landmark review, Olagunju’s contributions help demystify how organizations can effectively transform raw, disparate data into actionable business intelligence. His work is particularly notable for its clarity and practical utility, making complex data architecture decisions more accessible. For students and researchers entering the field, Olagunju’s research serves as an essential starting point for understanding the evolving landscape of data integration and its critical role in powering data-driven decision-making.