With databases and data records growing at an exponential rate, business analysts spend a lot of their time trying to sift through large datasets in an effort to generate insights for their business’ products and/or services. In many cases, data providers copy or mirror their data sets so that end users (internal or external) have the ability to analyze the data in a manner that may not be secure or anonymized. This process can be inefficient especially when only a certain segment of data from the dataset needs to be analyzed.

York University researchers have created a privacy-protected, data sharing platform (Bitnobi) that alleviates all of these issues by providing a solution that allows data providers to share access to data in a secure manner without releasing raw data or making copies of them. Furthermore, the platform enables the data provider to control access to virtualized segments of data so that end users (business analysts, data scientists etc.) can choose the data they want to work with in building a data job instead of acquiring a data provider’s entire data set. The end user leverages a simple, easy-to-use interface so that they can build and launch data jobs quickly on the data provider’s infrastructure. Bitnobi will provide an organization with a large amount of data with the ability to share and process data in an efficient/secure manner.