Sharing Data Intelligence Without Sharing Sensitive Data

Creating business intelligence out of data resources has become both a key strategy for most organizations as well as a major challenge as organizations struggle to find a way to protect confidential and regulated data that are used to build the business intelligence and analytical analysis. Often the data may contain sensitive data critical to organizing the business intelligence, but not critical to the overall findings or outcomes. For example, in order to identify trends on customer preferences, there may be a need to use social security numbers to correlate data from different data sources. While it is the trends that provide the useful business intelligence, the challenge is finding a way to analyze and share the relevant trends without compromising the sensitive information included in the data, such as social security numbers. 

While past efforts focused on anonymizing the data, this still creates a challenge in that the sensitive data may still be exposed to the analysts or others who also should not have access to the confidential and regulated data but are involved in the process of creating the anonymized result. Additionally, the anonymizing efforts require more time and resources to create a new version of the data.  

The OnData platform provides an automated approach to efficiently and cost effectively prepare data for building critical business and analytical intelligence without ever exposing any confidential and regulated data to anyone who does not have the correct permissions to access such data. The OnData technology allows an organization to make data insights available without ever having to worry about exposing any confidential or regulated data. 

Specifically, the OnData platform provides automated options for protecting confidential and regulated data that are used by your existing business intelligence and analytical technology tools. OnData easily integrates with your existing technology solutions to seamlessly protect any confidential or regulated data by leveraging OnData’s field categorization and encryption features. For example, using OnData’s application agnostic encryption will protect confidential and regulated data as it is loaded to the business intelligence/data warehouse environment. Alternatively, OnData’s tools can dynamically encrypt or mask the confidential and regulated data as it is called by a user. Such data is protected before it is shown to the user. These OnData features enable data consumers to create business intelligence and analytics from existing data sets without requiring IT time and resources to create additional data sets in order to protect confidential and regulated data.