The rapid expansion of big data systems presents both tremendous opportunities and significant challenges for organizations. As these systems handle increasingly large volumes of sensitive data, effective risk management becomes critical to ensuring their security, scalability, and compliance. This paper proposes a structured framework for enhancing risk management in big data investments, addressing key risks such as security vulnerabilities, compliance challenges, and operational inefficiencies. The framework integrates advanced technologies, including AI-driven anomaly detection, zero-trust security models, and cloud-based scalability solutions, to provide a holistic approach to safeguarding data while enabling the growth and performance of big data systems. Through a detailed exploration of organizations' risks and challenges, this paper outlines strategies for mitigating security threats, ensuring regulatory compliance, and maintaining operational continuity as data systems expand. The proposed framework offers actionable recommendations for businesses, policymakers, and technology leaders to ensure secure and scalable big data investments.