Securing Data Platforms in B2B Enterprises: A Framework for the Protection of Customer Data

In business-to-business (B2B) enterprises, the development of data platforms for processing customer data is increasingly common. These platforms ingest data into a diverse array of relational and nonrelational data stores, data lakes, and data warehouses. The processing phase employs a varied set of technologies encompassing streaming and batching technologies. The resulting processed data are stored in a multitude of formats, serving diverse purposes, such as deriving analytics, creating training datasets for machine learning models, and building data products for customers. Throughout the data lifecycle, the data encounters various touchpoints with engineers and other employees who have access to it, emphasizing the critical need for enterprises to protect these data. [1] Traditional methods of encrypting data and implementing data access controls may fall short, given the myriad ways in which data are consumed. [2] Furthermore, despite individual technologies offering data protection mechanisms, there is a distinct lack of a comprehensive and holistic approach that encompasses the entire data platform. These technology-specific measures are insufficient for adequately addressing the diverse use cases encountered in real-world scenarios. This study addresses the critical need for robust security measures in data platforms, proposing a comprehensive framework with five key pillars: data masking, data cataloging, data offboarding, data access control and data auditing. Our approach ensures the protection of both the structured and unstructured customer data processed on these platforms. Data Masking safeguards sensitive information, while Data Cataloging provides efficient organization and central cataloging of diverse data assets. Data Offboarding is essential for the secure and compliant deletion of customer data at the end of the data lifecycle, and the Audit pillar ensures ongoing monitoring and adherence to regulatory standards. This framework is especially relevant for B2B enterprises, where customer data security is not only a regulatory obligation, but also fundamental to maintaining trust and business integrity. By presenting a detailed strategy for protecting customer data on these platforms, this study aims to guide B2B enterprises in implementing effective security measures, thereby ensuring the confidentiality, integrity, and compliance of vital data assets in an increasingly data-centric business world.