What is real data intelligence? It spawns from the idea of data democratization, allowing stakeholders from across an organization access to data and removing the notion of IT departments as the gatekeepers of data. The democratization of data within an organization relies upon a deep understanding of the data and has led to the rise in automated data discovery tools and data catalog solutions to find data and populate centralized data inventories. Allowing stakeholders direct access to data has helped organizations to have a much greater understanding of their data as well as driving additional business value from their data. However, it also brings additional risks that need to be considered. This is where real data intelligence becomes essential.

It seems like an almost weekly occurrence that new data protection and security laws are introduced for organizations to be mindful of, creating new obligations for processing data and adding additional layers of complexity for those accessing the data. Real data intelligence is derived from embedding privacy and security teams into the fabric of data governance programs, removing these functions from a silo, and understanding the business risks associated with openly accessible data. In sum, real data intelligence is a balancing act of having a deep understanding of your data and the privacy and security risk associated with that data.

Register for the webinar: Building a Path to Data Intelligence on April 6 at 11 am EDT/4 pm BST 

Automated and Agile Understanding of Data

Encouraging innovation, discovering business insights, and finding additional value from data are the main drivers for many organizations seeking to democratize their data. Introducing this agile use of data across an organization requires data mapping and inventory exercises to be fully automated in order to deepen an organization’s data intelligence. Automating data discovery and data mapping can help answer what data influences the organization and how it can influence the organization. Yet, these exercises and automation alone will not answer what types of risk this data brings an organization or help understand what that risk means.

The inner relationship between a data catalog and the data map does allow organizations to answer questions such as:

  • Where is this data coming from?
  • Where is it now?
  • How did it get there?
  • What is the quality of this data?
  • What risk does it pose to the business?

But, for an organization to have a grasp on real data intelligence, the ability to scale with modern data ecosystems by using modern computing concepts; the ability to create an agile governance program by validating the data dictionary and, in turn, data catalog with an empirical baseline of actual data; and the ability to find a balance between mitigating risk from data regulations and cyber threats while enabling faster access to higher quality data, all need to be addressed in the same breath. They’re not separate conversations, done by individual parts of an organization. Privacy, security, and governance teams need to work in unison with fully automated and integrated technologies because if you do not understand what data you have, where it’s stored, and what it means to the business then the data is of little use to the organization.

Register for your local event: DataConnect 2021

Importance of Compliance for Real Data Intelligence

Automation and agility play a big part in understanding and using data as quickly and effectively as possible and knowing that you are able to trust that data to be accurate. Where real data intelligence comes into play is understanding whether or not this data is putting the company at some type of risk, what that risk is, and understanding if that is data good enough to justify taking that risk.

Having the automated capability to grant access to every user across the organization, to completely understand what data you have, and to completely understand how this data is being used effectively without increasing risk to the company are the fundamental elements of real data intelligence.

Real data intelligence can and should be seen as a by-product of a strong trust program within an organization. Privacy, security, and governance teams working towards a common goal of empowering organizations to make data-driven business decisions while minimizing risk are fundamental in building consumer trust, and truly having a holistic understanding of your data.

In summary, real data intelligence is a comprehensive view of data across all disciplinary functions within an organization. OneTrust Data Governance seamlessly integrates with OneTrust’s wider privacy, security, ethics, and GRC solutions to give all business functions a clear view into the data they need,  helping to foster a culture of trust across the organization.

To learn more about how OneTrust DataGovernance can help your organization develop real data intelligence, request a demo or register for the webinar ‘Building a Path to Data Intelligence’.

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