Automated Data Governance

Drivers for Automated Data Governance and Privacy

DataSkill has found that data-driven decision making relies on speed. Competitive advantage is achieved by discovering insights and taking action before your competitors. To meet the demand for data, privacy and security decisions need to be made in real time. Within a continually changing business landscape, the only way to meet this time constraint is to implement a unified data privacy framework integrated with AI-led automation. Let’s take a look at some of the drivers for automated data governance and privacy.

Data privacy at scale

With ever expanding volumes of data, from a widening geographical area and covering an increasing variety of data types – data privacy at scale is complex. Reacting to every challenge individually is time consuming. Implementing a holistic organization wide approach to privacy through an automated governance layer can speed up time to compliance, by defining access in one single place. Changing regulations can be automatically ingested and applied to workflows. Routine, manual governance activities can be automated, providing a consistent and trusted approach.

Improve data access

Data needs to be accessible to multiple teams across the organization in a secure and traceable way. Each individual team needs to trust not only the integrity of the data, but also the security of the data. If this trust isn’t achieved then the individual teams are unlikely to share their data, creating further data silos. In addition, if the individual teams create their own protection systems for the data, this adds further complexity to already complex systems. Automatic tagging sensitive data allows it the be masked, so it is nonidentifiable to users/systems and only visible to those who need to see it.

Maintain data quality standards across the organization

The quality of the data affects users’ confidence to act. In order to invest in a proposed action, the data needs to be trustworthy. Only with access to fresh, clean, and relevant data can accurate business decisions be made. Business data needs to be discovered, catalogued, and transformed. Through business definitions and metadata, the data is more consistent and fit for purpose. Automated metadata generation allows the origin, privacy, age, and potential users of data to be tracked. Manually generating metadata is an unwieldy process. Automating this process makes it far more manageable and mitigates human error.

Data lineage and traceability

Data lineage shows where data comes from, how it has been accessed and who by. Increasingly such information is required for audit purposes. In some jurisdictions, privacy regulations require analytics teams to trace data through all its transformations, from where it was first created up to its use in the decision-making process. This traceability of data has the additional benefit that it can build trust in the data.

Facilitate data consumption

Self-service data consumption allows data users to find appropriate data quicker. They can start querying the data straight away without having to wait for a data engineer to prepare it. Using machine learning, automated cataloging continually identifies and connects data across the organization. This data catalog simplifies access to data and frees the data consumers up to focus on uncovering insights to make intelligent decisions.

DataSkill recommends IBM Cloud Pak for Data. IBM Cloud Pak for Data is a data fabric solution that connects the right data, at the right time, to the right people, from anywhere it’s needed. It simplifies and automates data collection, organization, and analysis. With IBM Cloud Pak for Data organizations can eliminate complexity by centralizing the definition of policies and automating the deployment and enforcement of those polices globally. It allows self-service access to trusted data, while reducing compliance risks. It’s cloud-native design and Red Hat Openshift foundations mean that IBM Cloud Pak for Data can be deployed anywhere including on-premises, hybrid cloud or private cloud.
IBM Cloud Pak for Data makes it easy to find, use, prepare and share data among your team members in a secure way. With DataSkill and IBM Cloud Pak for Data users can start accessing insights to make intelligent decisions.