This research investigates the causal relationship of big data management with the organizational performance of Zenith Bank, Nigeria Plc. The primary aim was to assess how the components of big data management--storage, visualization, and analytics--enhance the bank’s operational efficiency and overall performance. A cross-sectional survey research design was employed, relying on primary data collected from management personnel at Zenith Bank branches in Delta State, Nigeria. Using a census sampling approach, the entire population of 32 management staff was included in the sample. The data were analyzed through linear regression techniques. The findings revealed that all three aspects of big data management--storage, visualization, and analytics--positively and significantly contribute to the bank’s performance. The study concludes that effective big data management is a strategic asset that fosters operational efficiency, promotes data-driven decision-making, and enhances organizational growth. It is recommended that financial institutions prioritize investments in advanced big data tools and infrastructure to maintain competitive advantages and achieve superior performance in an evolving financial landscape.

Big data management, big data analytics, big data visualization, big data storage, organisational performance

https://doi.org/10.58396/pjbm020104 

[1]       H. Allioui and Y. Mourdi, “Unleashing the potential of AI: Investigating cutting-edge technologies that are transforming businesses,” Int. J. Comput. Eng. Data Sci., vol. 3, no. 2, pp. 1-12, 2023.

[2]       P. Bedi and D. Toshniwal, “Prescriptive analytics: An overview and a case study,” Int. J. Inf. Manage., vol. 45, pp. 203-216, 2019.

[3]       M. Bharadiya, “AI and machine learning in big data analytics,” J. Emerg. Technol., vol. 12, no. 1, pp. 45-57, 2023

[4]       S. Mifalef et al., “Technological advancements in banking data management,” Banking Technol. Rev., vol. 12, no. 4, pp. 78-95, 2021

[5]       M. Brady, “Big data technologies in financial services,” Int. J. Financ. Stud., vol. 7, no. 2, pp. 56-70, 2019

[6]       M. Mariani and S. F. Wamba, “Exploring how big data analytics can enhance dynamic capabilities,” J. Organ. Change Manage., vol. 31, no. 2, pp. 456-474, 2018

[7]       F. Ciampi, V. Cillo, R. Rialti, and L. Zollo, “Big data analytics for management: A practical application,” J. Bus. Res., vol. 131, pp. 305-314, 2021

[8]       R. Ranjan and C. Foropon, “Big data analytics in banking: A literature review,” J. Bus. Res., vol. 131, pp. 241-254, 2021

[9]       D. Lasater, J. Wang, and L. Rodriguez, “Optimizing resources for organizational performance,” J. Manage. Dyn., vol. 22, no. 3, pp. 140-155, 2019

[10]    S. Dutta, "Big data analytics in investment decision making," Financ. Anal. J., vol. 80, no. 1, pp. 89-102, 2024

[11]    F. Arena and G. Pau, “An overview of big data analysis,” Bull. Electr. Eng. Inform., vol. 9, no. 4, pp. 1646-1653, 2020

[12]    S. Batistič and P. van der Laken, “History, evolution and future of big data and analytics: A bibliometric analysis of its relationship to performance in organizations,” Br. J. Manage., vol. 30, no. 2, pp. 229-251, 2019

[13]    M. Comuzzi and A. Patel, “How organizations leverage big data: A maturity model,” Ind. Manage. Data Syst. J., vol. 116, no. 8, pp. 1468-1492, 2016

[14]    U. Egham, "Gartner identifies top 10 data and analytics technology trends for 2020," Gartner Newsroom, Jun. 22, 2020. [Online]. Available: https://www.gartner.com/en/newsroom/press-releases/2020-06-22-gartner-identifies-top-10-data-and-analytics-technolo. Accessed: Dec. 1, 2024

[15]    V. Grover, R. H. L. Chiang, T. Liang, and D. Zhang, "Creating strategic business value from big data analytics: A research framework," J. Manage. Inf. Syst., vol. 35, no. 2, pp. 388-423, 2018

[16]    M. Ghasemaghaei and G. Calic, "Assessing the impact of big data on firm innovation performance: Big data is not always better data," J. Bus. Res., vol. 108, pp. 147-162, 2020

[17]    M. A. Khan and L. Wang, "Big data analytics: Concepts and applications," J. Big Data, vol. 8, no. 1, p. 56, 2021

[18]    A. Elegendy, J. Yu, R. C. Wong, and R. Sarkar, "Big data analytics for enterprise growth," Enterp. Technol. Rev., vol. 8, no. 3, pp. 15-29, 2022

[19]    S. Yu, P. K. Wong, and R. Sarkar, “Big data applications in financial decision-making,” Journal of Financial Analytics, vol. 5, no. 3, pp. 112-130, 2021

[20]    M. Seyedan and K. Mafakher, “A review on big data analytics and its applications in various industries,” J. Big Data, vol. 7, no. 1, p. 48, 2020

[21]    R. Cioffi, M. Travaglioni, G. Piscitelli, A. Petrillo, and A. Parmentola, "Big data analytics: A critical perspective for business applications," J. Bus. Econ., vol. 90, no. 4, pp. 1025-1045, 2020

[22]    M. Tula, O. Ogunnaiya, and T. Adeyemo, “Advancements in big data analytics tools,” African Journal of Data Science, vol. 11, no. 1, pp. 101-118, 2024

[23]    J. Patterson and V. Nolet, “Enhancing decision-making through AI-powered big data analytics,” Decis. Support Syst., vol. 136, p. 113356, 2020

[24]    M. Nocker and V. Sena, “Data integration and interoperability challenges in big data analytics,” Technol. Forecast. Soc. Change, vol. 148, p. 119734, 2019

[25]    G. Stanton and A. Stanton, “Staged integration for effective big data analytics,” Data Science Journal, vol. 18, no. 1, p. 15, 2019

[26]    B. Niu, Y. Wang, Y. Zhang, and J. Li, “Best practices in big data analytics adoption,” J. Organ. Analyt., vol. 10, no. 2, pp. 178-195, 2021

[27]    S. Shamim, Z. Pervez, and Y. Jiang, “Big data analytics capabilities and firm performance,” J. Bus. Res., vol. 120, pp. 23-31, 2020

[28]    M. J. Sousa and Á. Rocha, “Big data analytics and its role in enhancing organizational effectiveness,” Procedia Comput. Sci., vol. 164, pp. 723-730, 2019

[29]    T. B. Chandra and A. K. Dwivedi, “Data visualization: Existing tools and techniques,” in Advanced Data Mining Tools and Methods for Social Computing, Academic Press, 2022, pp. 177-217

[30]    H. Shabbir and F. Gardezi, “Organizational performance and operational profitability,” Int. Rev. Bus. Res., vol. 8, no. 4, pp. 45-59, 2020

[31]    G. C. Nwokocha and D. Legg-Jack, “Reimagining STEM education in South Africa: Leveraging indigenous knowledge systems through the m-know model for curriculum enhancement,” Int. J. Soc. Sci. Res. Rev., vol. 7, no. 2, pp. 173-189, 2024

[32]    O. A. Adenekan, N. O. Solomon, P. Simpa, and S. C. Obasi, “Enhancing manufacturing productivity: A review of AI-driven supply chain management optimization and ERP systems integration,” Int. J. Manage. Entrepreneursh. Res., vol. 6, no. 5, pp. 1607-1624, 2024

[33]    S. Pandey, R. K. Singh, A. Gunasekaran, and A. Kaushik, “Cyber security risks in globalized supply chains: Conceptual framework,” J. Global Oper. Strateg. Sourc., vol. 13, no. 1, pp. 103-128, 2020

[34]    T. O. Jejeniwa and N. Z. Mhlongo, "The role of ethical practices in accounting: A review of corporate governance and compliance trends," Finance & Account. Res. J., vol. 6, no. 4, pp. 707-720, 2024

[35]    D. Simpa, et al., “Implementing big data visualization in business: A comprehensive guide,” Available: https://sumatosoft.com/blog/implementing-big-data-visualization-in-business, accessed Dec. 1, 2024

[36]    O. Okonewa and P. C. Umenzekwe, “Audit quality and accounting going concern of listed financially distressed and financially healthy manufacturing companies in Nigeria: A comparative study,” J. Res. Bus. Manage., vol. 12, no. 4, pp. 1-18, 2024

[37]    N. S. Uzougbo, C. G. Ikegwu, and A. O. Adeusi, “Legal accountability and ethical considerations of AI in financial services,” GSC Advanced Research and Reviews, vol. 19, no. 2, pp. 130-142, 2020

[38]    C. V. Ibeh, O. F. Asuzu, T. Olorunsogo, O. A. Elufioye, N. L. Nduubuisi, and A. I. Daraojimba, "Business analytics and decision science: A review of techniques in strategic business decision making," World J. Adv. Res. Rev., vol. 21, no. 2, pp. 1761-1769, 2024

[39]    M. Cieslik and T. Margoesy, "Big data storage: Ethics and innovation," Int. J. Data Manage., vol. 7, no. 3, pp. 120-135, 2022

[40]    W. Zhang, X. Li, and H. Chen, “DNA storage: Exploring the future of molecular data preservation,” Journal of Advanced Storage Solutions, vol. 10, no. 7, pp. 1025-1040, 2022

[41]    A. Adadi, “The role of big data in banking,” J. Bank. Finance, vol. 45, no. 3, pp. 123-135, 2021

[42]    B. Bhushan, “A comprehensive overview of magnetic data storage: Past, present, and future,” J. Data Storage Technol., vol. 15, no. 2, pp. 45-60, 2018

[43]    A. Hussain, M. Khan, and F. Rehman, "Cloud computing in data backup and restoration," Int. J. Inf. Syst., vol. 20, no. 4, pp. 78-93, 2023

[44]    R. Gupta, P. Sharma, and S. Verma, "Cloud computing and big data: Synergy for innovation," J. Cloud Comput., vol. 11, no. 1, pp. 25-42, 2022

[45]    M. Prabhu and T. Rajesh, “Addressing data security challenges in cloud computing,” J. Secure Comput., vol. 12, no. 3, pp. 89-104, 2020

[46]    X. Wei, J. Liu, and L. Zhang, “Edge computing in power systems: Enhancing stability and efficiency,” Journal of Smart Infrastructure, vol. 8, no. 2, pp. 150-170, 2021

[47]    P. Padgavankar, “Advances in network-based storage: A focus on NAS and SAN,” Int. J. Netw. Storage, vol. 6, no. 5, pp. 201-215, 2020

[48]    O. B. Seyi-lande, E. Johnson, G. S. Adeleke, C. P. Amajuoyi, and B. D. Simpson, “The role of data visualization in strategic decision making: Case study from the tech industry,” Comput. Sci. IT Res., vol. 5, no. 6, pp. 1374-1390, 2024

[49]    P. C. Umenzekwe, A. G. Nwosu, and O. Okonewa, “Corporate social responsibility and financial performance of Dangote Cement in the pre and post COVID-19 pandemic period,” Journal of Management Sciences, vol. 60, no. 2, pp. 1-11, 2023

[50]    R. Dubey, A. Gunasekaran, and S. J. Childe, "Market power and business style as predictors of organizational performance," J. Supply Chain Manage., vol. 10, no. 4, pp. 255-272, 2019

[51]    S. Anwar and A. Abdullah, “Factors influencing organizational performance: A focus on market competitiveness and employee satisfaction,” J. Bus. Res., vol. 18, no. 3, pp. 45-60, 2021

[52]    M. Hashmi, S. Akhtar, and T. Raza, "Operational outcomes and profitability in organizational performance," J. Bus. Admin., vol. 19, no. 1, pp. 67-82, 2021

[53]    K. Behloch and M. Rashi, “Organizational performance and growth phases: Aligning with strategic objectives,” Strateg. Manage. J., vol. 27, no. 4, pp. 89-104, 2022

[54]    S. Iqbal, R. Khan, and N. Ahmad, "Market capture as a determinant of organizational performance," Int. J. Bus. Econ., vol. 14, no. 3, pp. 120-135, 2018

[55]    S. Rehaman, Z. Ali, and M. Khan, “Future-oriented outcomes and organizational performance,” Organ. Stud. Rev., vol. 11, no. 6, pp. 25-39, 2019

[56]    S. P.-J. Wu, Q. Hu, and D. Yang, “Assessing organizational performance through efficacy and efficiency,” Journal of Organizational Effectiveness, vol. 15, no. 2, pp. 78-92, 2020

[57]    P. Dhamija and S. Bag, "Operational efficiency and its role in organizational performance: The impact of training," Int. J. Oper. Manage., vol. 12, no. 5, pp. 75-90, 2020

[58]    B. George, S. Chowdhury, and X. Huang, "Understanding organizational performance: Achieving long-term objectives," Manage. Sci. Q., vol. 34, no. 2, pp. 88-102, 2019

[59]    D. J. Teece, G. Pisano, and A. Shuen, “Dynamic capabilities and strategic management,” Strategic Management Journal, vol. 18, no. 7, pp. 509-533, 1997

[60]    S. Chatterjee, V. Mookerjee, and M. Gupta, “Dynamic capabilities and big data in financial institutions: An evolving perspective,” J. Strateg. Inf. Syst., vol. 32, no. 1, pp. 1-16, 2023

[61]    N. Ochuba, O. Amoo, E. Okafor, O. Akinrinola, and F. Usman, “Strategies for leveraging big data and analytics for business development: A comprehensive review across sectors,” Comput. Sci. IT Res. J., vol. 5, no. 3, pp. 562-575, 2024

[62]    B. Igbal, "Applying big data and supply chain innovation for organizational performance," South Asian J. Oper. Logist., vol. 3, no. 2, pp. 100-112, 2024

[63]    H. Gallo, A. Khadem, and A. Alzubi, "The relationship between big data analytic-artificial intelligence and environmental performance: A moderated mediated model of green supply chain collaboration (GSCC) and top management commitment (TMC)," 2023. [Online]. Available: https://onlinelibrary.wiley.com/doi/10.1155/2023/4980895. Accessed: Dec. 1, 2024

[64]    A. Latif, R. Fairdous, R. Akhtar, and M. Ambreen, “Exploring the impact of big data analytics on organizational decision-making and performance: Insights from Pakistan’s industrial sector,” Pak. J. Humanit. Soc. Sci., vol. 11, no. 2, pp. 1760-1779, 2023

[65]    B. Hawash, U. A. Mokhtar, Z. M. Yusof, and M. Mukred, "Enhancing business continuity in the oil and gas industry through electronic records management system usage to improve off-site working: A narrative review," J. Inf. Sci. Theory Pract., vol. 10, no. 2, pp. 30-44, 2022

[66]    H. Al-Malahmeh, “Influence of business intelligence and big data on organizational performance,” J. Syst. Manage. Sci., vol. 12, no. 5, pp. 193-212, 2022

[67]    A. Aljumah, “Exploring nexus among big data analytic capability and organizational performance through mediation of supply chain agility,” Uncertain Supply Chain Manage., vol. 10, pp. 999-1008, 2022

[68]    M. Al-Darras and C. Tanova, “From big data analytics to organizational agility: What is the mechanism?” SAGE Open, vol. 2022, pp. 1-18, 2022

[69]    S. Chatterjee, N. P. Rana, and Y. K. Dwivedi, “How does business analytics contribute to organisational performance and business value? A resource-based view.” [Online]. Available: https://bradscholars.brad.ac.uk/handle/10454/18377. [Accessed: Dec. 1, 2024]

[70]    L. B. Benjamin, P. Amajuoyi, and K. B. Adewusi, “Marketing, communication, banking, and fintech: Personalization in fintech marketing, enhancing customer for financial inclusion,” Int. J. Manage. Entrepreneursh. Res., vol. 6, no. 5, pp. 1687-1701, 2024