This work is licensed under a Creative Commons Attribution 4.0 International License.
Integrating Scientific Data Analytics into Digital Business Strategy
Corresponding Author(s) : Kursih Sulastriningsih
Startupreneur Business Digital (SABDA Journal),
Vol. 5 No. 2 (2026): Startupreneur Business Digital (SABDA Journal)
Abstract
Amid the increasing complexity of the contemporary digital economy, organizations face growing challenges in transforming large volumes of data into actionable strategic insights. While data analytics has become an essential component of digital business operations, the integration of scientific analytical principles into strategic decision-making remains insufficiently explored. This study aims to develop a conceptual framework for integrating Scientific Data Analytics (SDA) into digital business strategy by synthesizing insights from strategic management and data analytics literature. Using a qualitative approach based on literature review and thematic content analysis, this study examines how analytical methods such as causal inference, predictive analytics, and evidence-based management can support strategic planning and organizational decision-making. The analysis identifies several key themes, including organizational alignment, analytical capability development, data governance, and the role of evidence-based decision-making in enhancing strategic adaptability. The study further highlights potential challenges related to organizational resistance, data quality, and algorithmic bias that may affect analytics adoption. Theoretically, this research contributes by proposing an integrated conceptual framework that connects data analytics capabilities with strategic management processes. Practically, the study offers conceptual guidance for managers and decision-makers seeking to strengthen data-informed strategic planning in digital business environments. The findings provide a foundation for future empirical research examining the relationship between scientific analytics integration and organizational performance.
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- E. D. Balogun, K. O. Ogunsola, and A. S. Ogunmokun, “An integrated data engineering and business analytics framework for cross-functional collaboration and strategic value creation,” ResearchGate, March, 2025.
- T. H. Alaskar, “Integrated ai and business analytics for sustaining data-driven and technological innovation: The mediating role of integration capabilities and digital platform,” Sustainability, vol. 17, no. 19, p. 8749, 2025.
- M. N. H. Mamun, “Role of ai and data science in data-driven decisionmaking for it business intelligence: A systematic literature review,” Available at SSRN 5402976, 2025.
- R. Basu, M. N. Aktar, and S. Kumar, “The interplay of artificial intelligence, machine learning, and data analytics in digital marketing and promotions: a review and research agenda: R. basu et al.” Journal of Marketing Analytics, vol. 13, no. 2, pp. 267–287, 2025.
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- L. Pratt, C. Bisson, and T. Warin, “Bringing advanced technology to strategic decision-making: The decision intelligence/data science (di/ds) integration framework,” Futures, vol. 152, p. 103217, 2023.
- M. Murod, S. Anhar, D. Andayani, A. Fitriani, and G. Khanna, “Blockchain based intellectual property management enhancing security and transparency in digital entrepreneurship,” Aptisi Transactions on Technopreneurship (ATT), vol. 7, no. 1, pp. 240–251, 2025.
- S. Murri, M. Bhoyar, G. P. Selvarajan, and M. Malaga, “Transforming decision-making with big data analytics: Advanced approaches to real-time insights, predictive modeling, and scalable data integration,” International Journal of Communication Networks and Information Security, vol. 16, no. 5, pp. 506–519, 2024.
- I. A. Adeniran, C. P. Efunniyi, O. S. Osundare, A. O. Abhulimen, and U. OneAdvanced, “The role of data science in transforming business operations: Case studies from enterprises,” Computer Science & IT Research Journal, vol. 5, no. 8, pp. 2026–2039, 2024.
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- U. S. Nwabekee, O. Y. Abdul-Azeez, E. E. Agu, and T. I. Ijomah, “Digital transformation in marketing strategies: The role of data analytics and crm tools,” International Journal of Frontline Research in Science and Technology, vol. 3, no. 2, pp. 055–072, 2024.
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- R. Tarmizi, N. Septiani, P. A. Sunarya, and Y. P. A. Sanjaya, “Harnessing digital platforms for entrepreneurial success: A study of technopreneurship trends and practices,” Aptisi Transactions on Technopreneurship (ATT), vol. 5, no. 3, pp. 278–290, 2023.
- Q. Pang, J. Du, M. Fang, and L. Wang, “Strategic mechanism for enhanced sustainable practice performance in shipping organizations through big data analytics powered by artificial intelligence,” Journal of Enterprise Information Management, vol. 39, no. 1, pp. 188–213, 2026.
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- S. Bashang and K. Puttanna, “The role of artificial intelligence in digital marketing: a review,” International Research Journal of Economics and Management Studies IRJEMS, vol. 2, no. 3, 2023.
- A. O. Adewusi, U. I. Okoli, E. Adaga, T. Olorunsogo, O. F. Asuzu, and D. O. Daraojimba, “Business intelligence in the era of big data: A review of analytical tools and competitive advantage,” Computer Science & IT Research Journal, vol. 5, no. 2, pp. 415–431, 2024.
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- C. Ziakis and M. Vlachopoulou, “Artificial intelligence in digital marketing: Insights from a comprehensive review,” Information, vol. 14, no. 12, p. 664, 2023.
- H. Safitri, S. Audiah, and D. Edmond, “Digital marketing strategy in digital business to enhance msme competitiveness,” Startupreneur Business Digital (SABDA Journal), vol. 5, no. 1, pp. 78–87, 2026.
- E. O. Eboigbe, O. A. Farayola, F. O. Olatoye, O. C. Nnabugwu, and C. Daraojimba, “Business intelligence transformation through ai and data analytics,” Engineering Science & Technology Journal, vol. 4, no. 5, pp. 285–307, 2023.
- T. I. Ijomah, C. Idemudia, N. L. Eyo-Udo, and K. F. Anjorin, “Innovative digital marketing strategies for smes: Driving competitive advantage and sustainable growth,” International Journal of Management & Entrepreneurship Research, vol. 6, no. 7, pp. 2173–2188, 2024.
- A. Ruangkanjanases, A. Khan, O. Sivarak, U. Rahardja, and S.-C. Chen, “Modeling the consumers’ flow experience in e-commerce: The integration of ecm and tam with the antecedents of flow experience,” Sage Open, vol. 14, no. 2, p. 21582440241258595, 2024.
- A. B. P. Kasmo, S. Mor, L. Nugroho, M. Rohadi, and A. Purnama, “Integrating corporate strategy with digital transformation, cybersecurity, and sustainability,” Jurnal Lemhannas RI, vol. 13, no. 1, pp. 52–68, 2025.
- Q. Aini, S. W. Dyatmika, M. H. R. Chakim, M. Khasanah, and Z. Queen, “Integration of artificial intelligence in digital marketing strategies based on business data analytics: Integrasi kecerdasan buatan dalam strategi pemasaran digital berbasis analisis data bisnis,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 6, no. 1, pp. 12–20, 2025.
- U. Rahardja, “Social media analysis as a marketing strategy in online marketing business,” Startupreneur Business Digital (SABDA Journal), vol. 1, no. 2, pp. 176–182, 2022.
- A. S. Bist, V. Agarwal, Q. Aini, and N. Khofifah, “Managing digital transformation in marketing:” fusion of traditional marketing and digital marketing”,” International Transactions on Artificial Intelligence, vol. 1, no. 1, pp. 18–27, 2022.
- E. Sulistyaningsih, “Improving human resources technology innovation as a business growth driver in the society 5.0 era,” ADI Journal on Recent Innovation, vol. 4, no. 2, pp. 149–159, 2023.
- E. Omol, L. Mburu, and P. Abuonji, “Unlocking digital transformation: The pivotal role of data analytics and business intelligence strategies,” International Journal of Knowledge Content Development & Technology, vol. 14, no. 3, pp. 77–91, 2024.
- P. A. Sunarya, U. Rahardja, S. C. Chen, Y.-M. Lic, and M. Hardini, “Deciphering digital social dynamics: A comparative study of logistic regression and random forest in predicting e-commerce customer behavior,” Journal of Applied Data Sciences, vol. 5, no. 1, pp. 100–113, 2024.
References
E. D. Balogun, K. O. Ogunsola, and A. S. Ogunmokun, “An integrated data engineering and business analytics framework for cross-functional collaboration and strategic value creation,” ResearchGate, March, 2025.
T. H. Alaskar, “Integrated ai and business analytics for sustaining data-driven and technological innovation: The mediating role of integration capabilities and digital platform,” Sustainability, vol. 17, no. 19, p. 8749, 2025.
M. N. H. Mamun, “Role of ai and data science in data-driven decisionmaking for it business intelligence: A systematic literature review,” Available at SSRN 5402976, 2025.
R. Basu, M. N. Aktar, and S. Kumar, “The interplay of artificial intelligence, machine learning, and data analytics in digital marketing and promotions: a review and research agenda: R. basu et al.” Journal of Marketing Analytics, vol. 13, no. 2, pp. 267–287, 2025.
A. B. P. Kasmo, S. Mor, L. Nugroho, M. Rohadi, and A. Purnama, “Integrating corporate strategy with digital transformation, cybersecurity, and sustainability,” Jurnal Lemhannas RI, vol. 13, no. 1, pp. 52–68, 2025. [Online]. Available: https://jurnal.lemhannas.go.id/index.php/jkl/article/view/1062
D. C. Ayodeji, O. Oladimeji, J. O. Ajayi, A. O. Akindemowo, B. O. Eboseremen, E. Obuse, A. O. Ogedengbe, and E. D. Erigha, “Operationalizing analytics to improve strategic planning: A business intelligence case study in digital finance,” Journal of Frontiers in Multidisciplinary Research, vol. 3, no. 1, pp. 567–578, 2022.
L. Pratt, C. Bisson, and T. Warin, “Bringing advanced technology to strategic decision-making: The decision intelligence/data science (di/ds) integration framework,” Futures, vol. 152, p. 103217, 2023.
M. Murod, S. Anhar, D. Andayani, A. Fitriani, and G. Khanna, “Blockchain based intellectual property management enhancing security and transparency in digital entrepreneurship,” Aptisi Transactions on Technopreneurship (ATT), vol. 7, no. 1, pp. 240–251, 2025.
S. Murri, M. Bhoyar, G. P. Selvarajan, and M. Malaga, “Transforming decision-making with big data analytics: Advanced approaches to real-time insights, predictive modeling, and scalable data integration,” International Journal of Communication Networks and Information Security, vol. 16, no. 5, pp. 506–519, 2024.
I. A. Adeniran, C. P. Efunniyi, O. S. Osundare, A. O. Abhulimen, and U. OneAdvanced, “The role of data science in transforming business operations: Case studies from enterprises,” Computer Science & IT Research Journal, vol. 5, no. 8, pp. 2026–2039, 2024.
M. R. Aulia, Z. Lubis, I. Effendi et al., “Leveraging quality management and partnership programs for technopreneurial success: Exploring their impact on msme performance,” Aptisi Transactions on Technopreneurship (ATT), vol. 5, no. 2, pp. 157 168, 2023.
S. D. Jankovic and D. M. Curovic, “Strategic integration of artificial intelligence for sustainable businesses: Implications for data management and human user engagement in the digital era,” Sustainability, vol. 15, no. 21, p. 15208, 2023.
U. S. Nwabekee, O. Y. Abdul-Azeez, E. E. Agu, and T. I. Ijomah, “Digital transformation in marketing strategies: The role of data analytics and crm tools,” International Journal of Frontline Research in Science and Technology, vol. 3, no. 2, pp. 055–072, 2024.
A. N. I. Purwanto and A. A. Hanif, “Strategic synergy: Integrating business management with computer science for competitive advantage,” TechComp Innovations: Journal of Computer Science and Technology, vol. 1, no. 1, pp. 10–18, 2024.
A. A. Adesina, T. V. Iyelolu, P. O. Paul et al., “Leveraging predictive analytics for strategic decision-making: Enhancing business performance through data-driven insights,” World Journal of Advanced Research and Reviews, vol. 22, no. 3, pp. 1927–1934, 2024.
A. Aldoseri, K. N. Al-Khalifa, and A. M. Hamouda, “Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges,” Applied Sciences, vol. 13, no. 12, p. 7082, 2023.
V. Jain, C. Verma, M. K. Agarwal, and A. Rajkumar, “Influence of content authenticity on long-term consumer loyalty in digital markets,” International Journal of Research & Technology, vol. 14, no. S1, pp. 608–628, 2026.
R. Tarmizi, N. Septiani, P. A. Sunarya, and Y. P. A. Sanjaya, “Harnessing digital platforms for entrepreneurial success: A study of technopreneurship trends and practices,” Aptisi Transactions on Technopreneurship (ATT), vol. 5, no. 3, pp. 278–290, 2023.
Q. Pang, J. Du, M. Fang, and L. Wang, “Strategic mechanism for enhanced sustainable practice performance in shipping organizations through big data analytics powered by artificial intelligence,” Journal of Enterprise Information Management, vol. 39, no. 1, pp. 188–213, 2026.
N. P. L. Santoso, R. Nurmala, and U. Rahardja, “Corporate leadership in the digital business era and its impact on economic development across global markets,” IAIC Transactions on Sustainable Digital Innovation (ITSDI), vol. 6, no. 2, pp. 188–195, 2025.
S. Bashang and K. Puttanna, “The role of artificial intelligence in digital marketing: a review,” International Research Journal of Economics and Management Studies IRJEMS, vol. 2, no. 3, 2023.
A. O. Adewusi, U. I. Okoli, E. Adaga, T. Olorunsogo, O. F. Asuzu, and D. O. Daraojimba, “Business intelligence in the era of big data: A review of analytical tools and competitive advantage,” Computer Science & IT Research Journal, vol. 5, no. 2, pp. 415–431, 2024.
P. A. Okeleke, D. Ajiga, S. O. Folorunsho, and C. Ezeigweneme, “Predictive analytics for market trends using ai: A study in consumer behavior,” International Journal of Engineering Research Updates, vol. 7, no. 1, pp. 36–49, 2024.
C. Ziakis and M. Vlachopoulou, “Artificial intelligence in digital marketing: Insights from a comprehensive review,” Information, vol. 14, no. 12, p. 664, 2023.
H. Safitri, S. Audiah, and D. Edmond, “Digital marketing strategy in digital business to enhance msme competitiveness,” Startupreneur Business Digital (SABDA Journal), vol. 5, no. 1, pp. 78–87, 2026.
E. O. Eboigbe, O. A. Farayola, F. O. Olatoye, O. C. Nnabugwu, and C. Daraojimba, “Business intelligence transformation through ai and data analytics,” Engineering Science & Technology Journal, vol. 4, no. 5, pp. 285–307, 2023.
T. I. Ijomah, C. Idemudia, N. L. Eyo-Udo, and K. F. Anjorin, “Innovative digital marketing strategies for smes: Driving competitive advantage and sustainable growth,” International Journal of Management & Entrepreneurship Research, vol. 6, no. 7, pp. 2173–2188, 2024.
A. Ruangkanjanases, A. Khan, O. Sivarak, U. Rahardja, and S.-C. Chen, “Modeling the consumers’ flow experience in e-commerce: The integration of ecm and tam with the antecedents of flow experience,” Sage Open, vol. 14, no. 2, p. 21582440241258595, 2024.
A. B. P. Kasmo, S. Mor, L. Nugroho, M. Rohadi, and A. Purnama, “Integrating corporate strategy with digital transformation, cybersecurity, and sustainability,” Jurnal Lemhannas RI, vol. 13, no. 1, pp. 52–68, 2025.
Q. Aini, S. W. Dyatmika, M. H. R. Chakim, M. Khasanah, and Z. Queen, “Integration of artificial intelligence in digital marketing strategies based on business data analytics: Integrasi kecerdasan buatan dalam strategi pemasaran digital berbasis analisis data bisnis,” ADI Bisnis Digital Interdisiplin Jurnal, vol. 6, no. 1, pp. 12–20, 2025.
U. Rahardja, “Social media analysis as a marketing strategy in online marketing business,” Startupreneur Business Digital (SABDA Journal), vol. 1, no. 2, pp. 176–182, 2022.
A. S. Bist, V. Agarwal, Q. Aini, and N. Khofifah, “Managing digital transformation in marketing:” fusion of traditional marketing and digital marketing”,” International Transactions on Artificial Intelligence, vol. 1, no. 1, pp. 18–27, 2022.
E. Sulistyaningsih, “Improving human resources technology innovation as a business growth driver in the society 5.0 era,” ADI Journal on Recent Innovation, vol. 4, no. 2, pp. 149–159, 2023.
E. Omol, L. Mburu, and P. Abuonji, “Unlocking digital transformation: The pivotal role of data analytics and business intelligence strategies,” International Journal of Knowledge Content Development & Technology, vol. 14, no. 3, pp. 77–91, 2024.
P. A. Sunarya, U. Rahardja, S. C. Chen, Y.-M. Lic, and M. Hardini, “Deciphering digital social dynamics: A comparative study of logistic regression and random forest in predicting e-commerce customer behavior,” Journal of Applied Data Sciences, vol. 5, no. 1, pp. 100–113, 2024.