What Are Data Protection Platforms?

Vincent Brandon, Data Coordinator
February 23, 2022

Data Protection graphic
Photo by macrovector on freepick.com

What is a data protection platform?

A data protection platform (DPP) is a suite of technologies to help organizations understand what data are available, how those data are accessed, and who or what has access to those data. A host of new concepts and systems design principles are coming together to make this possible. Three pillars often stand out, including Zero-Trust Engineering, Privacy, and Object Metadata and Mappings.

Zero-Trust Engineering

Zero-trust engineering (ZTE) is a bottom-up approach to building physical and digital infrastructure where actors are constantly challenged at every action. In practice, users do not know it is happening. They scan badges, use RSA keys, and log in when they start their machines. In the background, every door, file, request, and button click is tested against an authorization chain. The idea of ZTE is everyone has everything they are supposed to have and nothing else, helping prevent data leaks and reduce the organization’s attack surface.

Privacy

Privacy is hot in the news. Yet, again, users often have no idea if their actions are private or not. That is beginning to change. Legal requirements have driven innovations in zero-trust systems and encrypted communications to allow modern workflows and activity to operate in complete secrecy between collaborators. Encryption rules the day for privacy, obfuscating data at every step – leaving no point in the information lifecycle where attackers or accidents can leak plain text secrets or sensitive information.

Object Metadata and Mappings

Keeping data is not free. One of the first pain points in digitization is efficiently managing the volume of records. Metadata collections allow powerful de-duplication and access control features so organizations can save money, ensure privacy, and feed zero-trust consumers. Mappings build on metadata to feed interfaces and data aggregation systems, containing instructions on how to meld objects from different parts of the system and external world into a seamless, searchable space. Metadata and mappings also drive improvements in privacy and security as data falling through the cracks tend to sit unprotected, stagnant for years as a growing target.

Why Invest In Building or Licensing a DPP?

A functioning DPP drives cost reductions in developer starts (integrations) maintenance (infrastructure and data pipelines) while enabling higher productivity for its users and risk reduction for the organization. However, platform acquisition and maintenance are expensive.

Potential buyers should look out for a few things before making a significant investment. First, any software platform needs to enable increased productivity and significant cost reductions across the enterprise. Second, users need to use the tools that suit them while contributing to their enterprise knowledge base. Pre-built integrations can make that a much smoother process and save hundreds of thousands of dollars in long-term maintenance and deployment. Third, the more data, computing, and user use-cases the organization needs to manage, the higher overhead becomes. Without an adequate solution, the overhead of even a small addition to a complicated web of unstructured data can swamp the productivity benefits of integration. An effective DPP has a very controlled integration cost and should not surprise anyone with sudden multiplicative cost increases exceeding the raw object storage of new sources.

Palantir’s Foundry seems to be the leader in the space, but their licensing costs currently price out many smaller organizations. Airbnb builds its own suite of services, but bespoke solutions do not often translate. Have you found any interesting offerings? Ping us on Twitter @UTDataResearch.

References

IBM. (2022). IBM Home. Retrieved from https://www.ibm.com/downloads/cas/6EODENGR

Nammour, E. (2021). Automating Data Protection at Scale, Part 1. Retrieved from Medium: https://medium.com/airbnb-engineering/automating-data-protection-at-scale-part-1-c74909328e08

Palantir. (2022). Foundry. Retrieved from Palantir Home: https://www.palantir.com/platforms/foundry