Understanding and taking control of your data ecosystem [Q&A]

Data comes in many forms and may be structured or unstructured, sensitive or purely statistical. Whatever it looks like, you can only benefit from it if you know what you have, where to find it, and how to access it.

We spoke with Brett Hurt, the company’s CEO and co-founder data world Discuss how businesses can understand and get the most value from their data.

BN: What is the importance of AI data governance?

BH: AI data governance reduces data risk and drives more valuable AI outcomes. It does this by classifying AI use cases and verifying data reliability.

AI data governance can also help teams discover and protect sensitive data so they can stay compliant and avoid fines. Through artificial intelligence, teams can enforce data access policies to better control who has access to specific data.

Essentially, by ensuring that the data used in AI applications is reliable and well managed, it ultimately increases trust in AI systems.

BN: The knowledge graph is the foundation of your company’s data catalog. Can you explain what this is and how it can benefit your customers?

have Knowledge graph It is a complex representation of an organization’s entire data ecosystem. It connects and models metadata, processes, policies, people, and systems in a way that supports extensive automation.

As the basis for the data catalog, this architecture brings significant benefits to customers. It provides a more connected view of an organization’s data landscape: think rolling cameras versus static snapshots. The knowledge graph structure enhances the potential of artificial intelligence applications by providing rich context and relationships within data. Ultimately, it’s a tool that allows customers to gain deeper insights and make better use of their data assets.

BN: Can you explain how context engines create strategic advantage in today’s competitive landscape?

Choline value: situation engine Bridging the gap between general-purpose AI models and your organization’s specific needs. They make it possible to “Google” your own data. By providing relevant, organization-specific context, these engines make artificial intelligence more tailored and effective for individual businesses. Think about it, what competitive advantage would you have if you could ask your database questions like, “What was the ROI of Product X over the past five years, and how did it compare to the ROI of Product Y?”

BN: How does data.world differ from your competitors?

BH: We stand out from the competition due to our unique data management approach and artificial intelligence preparation. We are the only data catalog platform built on the knowledge graph architecture.

We are also a team of true scientists and innovators. We hold 76 patents and counting. We have been focused on AI-ready data that is accurate, explainable, and manageable—long before it became cool.

Our platform includes data cataloging, governance and data operations, all powered by knowledge graphs. We can unify disorganized data better than anyone.

We leverage artificial intelligence, automation, integration and partnerships to help organizations get the most from their data.

BN: Data sprawl has been a perennial problem facing enterprises today. How does data.world solve this problem?

BH: Organizations are definitely drowning in data, there’s no doubt about it. Data sprawl hinders productivity and obscures valuable insights.

Rather than trying to centralize all data in one place, data.world provides a unified data catalog platform that can consolidate various data silos and tools. The data stays where it is – which is nice! We know organizing your stuff is hard work and often doesn’t fall under a single authority.

That’s why our platform works independently. We connect models and disparate data sources to build a cohesive view of the enterprise data landscape. Our catalog acts as a single pane of glass, providing visibility into data assets dispersed across various systems, repositories and cloud platforms.
We know that when it comes to managing data sprawl, it’s more than just knowing where the data is. It’s about understanding what it means, where it comes from, and how it’s used. Tracking data movement and transformation across systems helps understand data flow and impact.

Like any modern data catalog, data.world is designed to handle large volumes of data from disparate sources, so we grow with our customers’ data ecosystems.

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