Compliance is urgent business. With more data protection regulations in effect and passing every year, the risk of not being compliant is too large for most businesses to take. In spite of this, most next-gen data privacy platforms available have hardly sped up traditional methods of achieving data compliance. 

The old way of handling data subject requests and compiling a data map, both critical components of data compliance, are labor-intensive manual processes that take months to complete and often do not result in comprehensive results. While technology has helped remove the manual part of these tasks, many systems have failed to do so in a timely manner.

The average onboarding time for a data privacy platform is over six months. Why so long when companies are actively trying to achieve compliance? The answer lies in the overly-meticulous methods most vendors use for data source discovery and data classification.

Data Source Discovery

The root of privacyops, data source discovery, is also arguably the most challenging part of the process. This needs to be done first when onboarding a privacy platform, as uncovering as complete an idea as possible of all the data sources within an organization is the only way to compile a comprehensive data map and set up the necessary integrations to monitor risk and handle DSRs. 

For most privacy vendors, their solution to data source discovery is to conduct a mix of SSO scans, cloud scans, and web scans to locate as many data sources as possible. Even done concurrently, this takes time, but more importantly, does not identify the vast majority of data sources. These types of scans typically only find managed systems and customer facing systems, meaning any unused dormant data sources go undetected. This often translates to something in the range of 50-60% of data systems discovered.

MineOS’s approach to data source discovery goes beyond SSO, cloud, and web scans to find roughly 95% of data sources within an organization. We manage this with our proprietary email navigator technology, which goes through the metadata of your company email inboxes to locate managed and unmanaged systems. 

Our email navigator also provides useful context for the data systems it locates, which can provide insight into which employees use certain systems and how often they are using them. You get all these insights and discoveries with the safety of the typical scans other vendors use, but with more complete results and in less than half the time. 

Since it only checks email metadata, our email technology does not access any of the content within emails, meaning it does not pick up on sensitive data or act as surveillance. We built the tech only to locate evidence of data systems, such as receiving emails from a SaaS or having an invoice from one within your inbox.

Smart Data Sampling & Data Classification

Data classification is the step where most privacy vendors really struggle with timing. They will end up getting you positive results eventually, but it will take months.

The reason it takes so long is because most will simply scan everything in an effort to put together the most complete data picture possible. Considering most organizations run hundreds of data systems, scanning all of them adds up to months of implementation time, even if your privacy software only uncovered 60% of data systems. 

The challenge does not stop there, however. Even as other data privacy software runs multiple deep scans to find data sources, those scans require followup with people across the organization to understand the access and usage of each system. This brings privacy professionals back to the days of manual data maps, where they’d need to issue surveys to stakeholders in various departments to get insights into how data systems were being used, and thus, gauge their risk and importance. 

Here, the information MineOS’s email navigator feeds into the system sets up organizations for quick success. Based on the interaction with employees, MineOS’s AI can accurately predict which people within the organization are “power users” for which data systems as well as which types of data likely reside within said systems, doing much of the legwork for users without extensively surveying the entire company on system usage. 

Our approach to data classification also relies on our smart data sampling, which brings further insights into what systems are being used for and the data within them. Running smart data sampling allows organizations, especially enterprises with absolutely gargantuan data stacks, to get a bird’s eye view of their data compliance without running complete scans on everything like other privacy vendors would do. 

This saves endless time, and results in a cheaper and easier experience as companies can go about choosing which systems to integrate and which to scan in a sensible way that arrives at the same end place as the exhaustive approach to scanning and integrations does. 

Privacy programs matter, and dragging out the process of instituting one because a privacy vendor gives you a 9-month estimate on how long it’ll take to implement the system is not the way to kickstart yours. 

Time is money, and compliance is reputation and trust. Get your privacy program running in weeks instead of months with MineOS’s data privacy innovations.