How Automation and AI Are the Heart of Modern Data Governance

This year’s Informatica World theme was “Where Your Data Comes to Life.” It felt particularly appropriate as we showed what modern data governance looks like for digitally transformed businesses. Attendees saw how they could realize the value of the data spread across their organization. They heard how successful innovators unleashed their potential for new insights. And they learned how they could plan and scale for the future.

Everyone talks about digital transformation and becoming data driven. But as we move from the vision to reality (and begin to reap the benefits of our investments), the conversation has shifted. Now people want answers to questions like:

• How can I meet compliance and regulatory standards in a rapidly changing environment?
• What’s the best way to allow data sharing and democratization?
• And how can we scale our analytics and digital business while maintaining visibility and control?

Let’s dig deeper into improving governance and modernizing your approach — and why it is essential.

Data governance has historically focused on risk and compliance. Over time, another pattern emerged: businesses found that they could achieve more intelligent and reliable business outcomes by fueling analytics with trusted data. And this was not random: these companies succeeded because they accelerated data delivery and got the right data into the hands of business decision-makers.

This means that today’s modern enterprise needs to run a digital business at scale.

As a result, the requirements of a modern data governance solution contain three key elements:

• Allow you to meet policy compliance, both internal mandates for data use and industry regulation
• Create opportunities for data sharing and democratization to connect data producers with consumers
• Scale analytics to grow a digital business while maintaining clear visibility and control
  

As we presented at Informatica World, these are the critical enablers for success:

• Observation can help you identify and solve issues in your data pipeline and gain insight into how data flows across the organization, and allow you to take quick action
• Automation of processes and procedures can help you accelerate data delivery
• AI can help improve analytics, leading to faster and more informed decision-making and dependable data-driven outcomes

With businesses focused on accelerating data pipelines for analytics and AI, data observability, automation and AI are critical for providing an operational view on trust and to scale digital business. There are a few good reasons for this.

A modern data governance solution will provide data quality and profiling capabilities that will allow you to discover critical issues to address, set data quality goals and act. Also, by allowing you to implement organizational standards through rule automation and execution, you can refine your data through cleansing, parsing and verification processes.

Measuring compliance using automation and AI is also necessary to identify business context and policy compliance — and to map data flow and use to organizational standards. With the right data observability solution, you can better monitor performance expectations through reporting tools such as threshold alerts and scorecards or across a lineage path and take action where needed.

In short, observability, automation and AI help you operate more reliably with data and ensure accurate business results by ushering in the next phase of modern data governance to help you scale your digital business successfully.

Ready to bring your data to life? Learn more about how we can help your business grow and scale with modern data governance.

• Register now for our webinar, “Data Observability: The Key to Successful Data and Analytics.”
• Learn how to “Unlock New Business Insights with a Cloud Data Marketplace.”
• Experience Cloud Data Governance and Catalog in action with this interactive demo.