Linking structured and unstructured data

No matter how much value you think you’re extracting from your data, you’re likely only scratching the surface. What’s accessible and actionable is just a small portion—think 20% visible versus 80% hidden beneath the surface.

The visible data is typically structured—rows and columns neatly organized in spreadsheets or relational databases. But the majority of data is unstructured—the narrative-rich content that reveals the true story within.

This narrative layer is where the real value lies. It adds depth, context, and tone, bridging the gap between quantitative metrics and qualitative insights. It’s the key to transforming a million-dollar asset into a billion-dollar opportunity.

Dynizer technology connects your structured and unstructured data into a unified, integrated platform. It seamlessly brings everything together, empowering you to unlock the full potential of your data for strategic decision-making.

A Dynamic Semantic Index

Semantics serves as the bridge that connects narrative data to concrete facts and figures. How does it work? At its core, semantics revolves around four fundamental elements: People, Things, Places, and Moments in Time—essentially, the Who, What, Where, and When.

In narrative data, these elements are further enriched by How and Why, which add crucial context. By identifying the Who, What, Where, and When within a narrative, you can uncover the facts and figures hidden within and seamlessly integrate them. This is precisely what Dynizer excels at.

Actions

Traditional relational data models struggle to manage the sheer volume and diversity of data generated daily, as they were never designed for such complexity. Dynizer, however, identifies key elements within narrative data and understands the contextual relationships that connect them. These elements, known as actions, form the core foundation of Dynizer’s innovative technology.

Dynizer dynamically constructs its own data action models in real-time while seamlessly expanding these models through smart import pipelines for both structured and unstructured data. Additionally, any new data introduced into the system is instantly and intelligently linked to the existing information, ensuring a cohesive and comprehensive data ecosystem.

Dynizer Query Language

Dynizer introduces its powerful query language: DQL. As an enhanced version of SQL, DQL redefines data interaction by focusing on the Who, What, When, and Where, delivering unparalleled flexibility. Seamlessly search structured and unstructured data within a single query and simplify complex joins like never before. What sets DQL apart is its ability to query across entire datasets, regardless of their storage format, unlocking limitless possibilities for data exploration.