“We now have a single, secure source of truth to run our business on. Databricks and BigQuery allow us to show the true value of our data to the company and Immuta allows us to do it securely and in full compliance. To top it off, we’re saving huge amounts of time and money in the process.”
What is Data Sharing & Collaboration?
Data sharing is the process of provisioning information from one party to another, either internally, externally, or via a data exchange platform.
In an interconnected world, sharing and collaborating on data sets is essential to achieving real-time analytics, faster innovation, cost efficiencies, and stronger partnerships. Ensuring data is shared securely so that it is used appropriately on the receiving end is a key responsibility of modern data teams.
The Data Sharing Challenge
Data analytics rarely occur in a vacuum. Analysts collaborate and share scripts, dashboards, and models as they attempt to extract value from data. However, most controls protect only the raw data, and fail to consider the security implications of production-level data. The downstream impacts could open organizations up to increased risk and compliance violations that may go unnoticed until it’s too late to mitigate them.
Gartner has predicted that “organizations that promote data sharing will outperform their peers on most business value metrics,” but it remains a challenge for organizations that lack the right tools and oversight. Particularly in highly regulated industries, like financial services and healthcare, balancing the need for speed with the need for privacy can hinder tasks ranging from trading analytics to public health interventions.
