Data sharing has truly transformative potential in virtually all industry verticals. Understanding user needs and using them to improve service offerings, increase conversions, and identify cost-savings are just some of the advantages that data sharing delivers, whether it’s between departments or with outside third-parties. Unfortunately, there are considerable obstacles to data sharing, including:
Regulatory compliance – All organizations that do business in California (CCPA) or the EU (GDPR) or deal with patient data (HIPAA) are subject to strict data protection laws. The penalties for not complying with these directives can include fines of up to hundreds of millions of dollars and loss of consumer trust.
Data security – Whenever data is being shared, especially with third parties, your organization loses control over what happens with that data and how it’s secured. This introduces considerable risk into your organization and, depending on the magnitude, this risk can possibly outweigh the benefits.
Speed of insight – The value of data is time-sensitive. That is, the longer data-driven business insight takes to reach someone who can use it, the less valuable it is. Data sharing can be severely hampered by issues that “slow down” data, such as lack of interoperability, incompatible data collection and querying protocols, and low-speed ETL processes. This element of data sharing is often overlooked as, technically, the data is still shared. But the hidden cost is how much value has been lost in transit.
Storage and resource investment – Data operations require considerable upfront investment and ongoing running costs before the benefits of data analysis and sharing can be seen. Therefore, making a case for consistent ROI is a challenge for most data functions, especially when competing for resources with other areas of the organization.
How data platforms help make data sharing a success
The solution to all of these issues, and many others, is the use of virtualized data platforms to handle data sharing. Data virtualization creates an interoperable data layer that draws together only the data needed for specific queries wherever it is located. It simultaneously improves data security by performing data operations inside secure containers, giving data administrators the ability to deploy fine-grained access controls over all data sharing.
Below are some of the major ways that data platforms make secure data sharing a success in practice.
Data regulations place strict usage obligations on how organizations collect, store, and share data. The risks introduced by non-compliance prevent the maximization of data value.
Energy utilities can benefit immensely from data sharing by using it to improve service delivery, identify the most efficient locations for infrastructure, and reduce costs through predictive maintenance. As we explored in this white paper, data platforms empower utilities, equipment manufacturers, and local governments to share critical system data that benefits all while also remaining compliant with data protection laws such as the GDPR and CCPA.
This is achieved through the uniform anonymization of personal identifying information (PII) and the creation of secure execution environments for the querying of shared data. In doing so, no PII is ever passed from one entity to another or at risk of being lost.
Secure access controls
Data is a major target for hackers across the world, especially high-value data such as the personal health information (PHI) used in the medical field. Since poor access controls are one of the primary attack vectors for hackers, data platforms can improve security and reduce risk by hardening access points.
The Health Insurance Portability and Accountability Act (HIPAA) regulates how PHI is used in the United States. It is one of the major inhibitors of data sharing in the medical community, slowing disease research efforts and preventing patients from receiving fully informed and timely treatment.
Secure data platforms enable medical organizations to comply with HIPAA in their data sharing by enforcing granular data access controls. These controls create strict access protocols, ensuring that the PHI involved in collaborations can’t be used elsewhere or removed from its appropriate context without explicit permission. It also allows the creation of audit trails that detail every time that data was accessed, who accessed it, and how they used it so organizations can trace the source of a breach.
Faster use of data
Data platforms gather all data together wherever it is located, leading to more streamlined processes and faster delivery of insights.
It’s not always possible for organizations to know which data will be useful and which won’t. As a result, large amounts of data get stored, which can quickly turn data lakes into data swamps, slowing data operations to the point of inaction.
McCormick, a Fortune 500 food multinational, found that virtualized data platforms enabled them to significantly increase the speed of data usage and improve insight velocity. Creating an interoperable middle layer between collection and analysis enabled data sharing and self-service data delivery for the departments that needed it most. What began as a way for data sharing to be improved with an external collaborator was soon scaled to the whole organization.
Cheaper storage and improved ROI
Using a virtualized data layer allows organizations to hold data in cheaper storage options without impacting speed. It also makes it easier to scale data operations.
Research commissioned for Dell showed that using a virtualized data setup in lieu of non-virtualized storage delivered a range of benefits, including increased efficiency and greater potential for scalability. Most importantly, however, was a cost savings of over 45% through lower support, software, and running costs, and an increase in productivity.
Take full advantage of data sharing with Intertrust Platform
Data sharing is a huge opportunity for all businesses to benefit from more in-depth business insight. Unfortunately, fast, effective, and cost-efficient data sharing is not yet the norm across most industries for a number of reasons. Secure data platforms, particularly the creation of virtualized data layers, can overcome many of these challenges.
Deploying data virtualization processes improves speed by reducing the need for data migration and slow ETL processes while also lowering storage costs. Plus, with data virtualization, all data sharing operations can be performed in complete compliance with relevant data security regulations.
- How does trusted data sharing work?
Ans: Data sharing is the process of making the same data resources available to many applications, users, or organizations. Data sharing includes a technical, practical, legal framework and cultural elements that facilitate secure access to data from various entities without compromising data integrity. A robust and secure data sharing technology will provide fine-grain access and governance control to ensure that only the information you want to share is being accessed by the right person at the right time.
- Can I disable a data sharing service?
Ans: Data sharing can be turned off in most settings by disabling the settings in a specific app or by viewing the settings in the device’s operating system.
About Abhishek Prabhakar
Abhishek Prabhakar is a Senior Manager ( Marketing Strategy and Product Planning ) at Intertrust Technologies Corporation, and is primarily involved in the global product marketing and planning function for The Intertrust Platform. He has extensive experience in the field of new age enterprise transformation technologies and is actively involved in market research and strategic partnerships in the field.