"Predictive Analytics of Big Data as a Digital Tool for Empowering Social Workers in Working with Communities and Organizations"

The social work profession is facing growing challenges in the digital transformation era, particularly in managing the vast amounts of data generated by social and organizational changes. This reality necessitates the adoption of advanced analytical tools capable of transforming data into actionable knowledge that supports informed decision-making. This paper addresses a central problem concerning the limited integration of predictive analytics of big data in empowering social workers to perform their roles effectively within communities and organizations. The study aims to highlight the role of predictive analytics as a scientific approach and a strategic digital tool that enhances professional interventions by forecasting social trends, anticipating risks, and designing proactive, evidence-based actions.
The paper adopts a descriptive–analytical methodology, combining a review of contemporary literature and global best practices on the application of predictive analytics in social work contexts. The expected results suggest that integrating predictive analytics within social work systems can significantly improve professional efficiency, service quality, and data-driven decision-making.
The practical implications emphasize the need to equip social workers with digital and analytical competencies and to develop intelligent information systems within communities and organizations, thereby advancing an innovative, evidence-based practice grounded in artificial intelligence and digital transformation.