Data privacy is a challenging issue. With an increasingly wary public, the knee-jerk reaction is to lock data down. This is a mistake, because it restricts data analysis and all the benefits it can bring. Companies must balance privacy concerns while freeing up their data to provide valuable insights.
Privacy is a vital part of the relationship organizations build with consumers, but the world needs more data sharing rather than less. Can companies, research institutions, and governments balance the need for quality datasets for the public good with respect for the privacy of the people creating data? With the right architecture, the answer is a resounding “yes.”
The state of privacy
A common public response to data breaches and misuse is to stop sharing data. For data to reach its potential, the public perception of data sharing has to change. The public has every right to data privacy, but responsible data sharing is essential for the public good.
What do people want?
The public wants to know that personal identifiers for sensitive data will be scrubbed. People also want to know that their data won’t become a liability for:
- Fraud: Data breaches cost millions of dollars for companies and the public.
- Manipulation: Disinformation is a cybersecurity issue. More consumers are becoming aware of the effects data quality has on public perception.
- Spying: 79% of consumers are afraid of government spying thanks to data proliferation, especially during Covid-19.
What do people need?
Despite these fears, data sharing is a public good. The responsible use of quality data allows cities and organizations to plan for disruption, enables research and innovation, and provides personalized services that consumers crave.
- Healthcare sharing: Public access to health data led to greater efficiency in discovering viable Covid-19 vaccines.
- Research sharing: The human genome project placed its findings immediately in the public domain, which led to nearly $800 billion in economic benefits.
- Economic sharing: Greater public access to data allows governments to allocate money to communities and individuals that need it most, and could prevent a repeat of 2020’s funds handling controversies.
Privacy versus the public good
Balancing privacy with data sharing is challenging. Even thinking of it as a balancing act can lead to a zero-sum game, in which any increase in one means a loss for the other.
Instead of a see-saw, organizations can use composable architecture with a data fabric to maintain privacy without restricting data flow, creating a carousel instead. Data never stops flowing, but access to the data is granted on an individual, case-by-case basis, using configurable rules and attributes. Move away from zero-sum and toward a system that improves both privacy and data sharing.
This architecture is especially important for healthcare data, which is already notoriously difficult to come by, leading to challenges with bio-research. Data privacy is a vital part of nurturing the public trust that helps make healthcare data available, but indiscriminate lockdowns of data have far-reaching repercussions.
For example, the rapid response to Covid-19 happened precisely because of public access to data. A Chinese laboratory identified and sequenced the novel Coronavirus in early 2020, and putting it into the public domain allowed researchers to move quickly, even without an actual sample. Combined with health data, vaccine development was faster than ever in our history.
On the other hand, the lack of data made it difficult for the government to dispense economic stimulus and relief. The government did not have real access to data that might facilitate relief based on need, leading to large businesses snapping up limited funds while small businesses went under. With better data, governments could direct future efforts more efficiently.
The evolution of data privacy
Instead of locking data away, organizations should leverage new tools to change the entire conversation surrounding privacy.
Composable architecture
A composable architecture allows organizations to shift to modular data pipelines. Institutions can scale operations up or down based on need, implement new components based on need, or remove ones that no longer serve without the system collapsing into loopholes.
Data Fabric
A data fabric ensures that companies can build in governance at a more granular level. This component eliminates security loopholes while providing access to data for anyone who needs it. In fact, a data fabric is essential for moving away from balancing privacy with access. Companies will be able to boost both.
A new approach to privacy
A modern approach to privacy protections allows organizations to release more data for social good. Consumers won’t need to worry that organizations will exploit their data, while researchers in critical fields such as healthcare will have access to data for training and research.
The Modern Data Company is working on the front lines of data privacy and data access. Our data fabric unlocks vital data with use cases in healthcare, government, retail, research, and more, but our approach puts security at the forefront. Organizations no longer need to sacrifice one for the other — they can achieve full data flow with absolute security. It’s a new era of data privacy.
Discover more about what Modern has accomplished in governance and security, and how DataOS helps ensure rigorous compliance by downloading our paper “Data Security and Governance in DataOS.”
