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An Introduction to GraphGrid

November 15, 2021

Ben Nussbaum

Learn about GraphGrid Connected Data Platform (CDP) and how it powers knowledge graphs and AI

Disparate data systems are a persistent problem in enterprise-level organizations.

The challenge isn’t to collect more data. After all, data lakes and warehouses are filled to the brim with unused information. What if, instead of gathering dust on a forgotten server somewhere, all that data could be harnessed to advance your organization’s mission? What if the untapped potential of your data could be unleashed simply by connecting it?

Connected data – data that has been enriched to show relationships – has the power to transform any organization by enriching current data elements and ensuring that new data collection doesn’t go to waste.

Of course in order to harness the power of connected data, you need an enterprise-grade connected data platform. Let’s take a closer look at how GraphGrid fits the bill.

Built for Builders

GraphGrid Connected Data Platform is a grid of modules built around the Open Native Graph Database (ONgDB). It gives you all the tools you need to harness your connected data and power mission-critical applications.

As a developer-first platform, GraphGrid puts your technical team in the driver’s seat to build and customize to your exact specifications. GraphGrid tutorials help developers get started with the platform, but from there, the only limit is their imagination.

Event-Driven Graph Capabilities

Connected Data Platform gives your developer team – and the solutions they build – real-time access to new information. Built-in integration services in GraphGrid distribute, route, and transform transactional event data to trigger dynamic searching, indexing, and machine learning processes.

These event-driven capabilities ensure that your graph data seamlessly integrates new information as it’s ingested. As a result, your data-driven tools react and respond to changes in real time. Bottom line: no more decisions based on stale data.

Manager

Manager allows your developers to design, create, and maintain a knowledge graph that meets your specific business needs. You can customize your model to match the shape of your data – and then edit that data model as your needs change. In addition, Manager gives your developers control of node types, relationship types, properties, and constraints to keep graph data uniform across your organization.

Also as part of Manager, GraphGrid gives your developers the power to create and control customized dynamic APIs called Showmes. These Showmes use Geequel™ – an open graph query language – to return targeted result sets of graph-based data for non-technical members of your team. These Showme queries can then be saved and reused by analysts in the future.

Showmes can be sequenced into chains to reveal complex data insights only attainable by diving deeper into the connected graph data. And as you introduce new data, a Showme incorporates it into the query results in real time.

Engineered to Connect Your Organization

GraphGrid also empowers your data analysts and less-technical personnel to harness the power of connected data.

By connecting disparate data sources, GraphGrid eliminates data silos and tribal knowledge in your organization. Furthermore, GraphGrid makes your data more understandable and actionable for a wide range of technical and non-technical users by representing data with a common language of people, places, and things.

Your data analysts can then use GraphGrid to get further insights from your data.

Search

With GraphGrid Search, your opportunities for data discovery are wide open. This tool works across your graph database, allowing you to define policies for populating search indexes based on highly customizable documents. In turn, these policies support the Geequel query language.

For your data analysts, using the Search feature is:

  • Easy: The plug-and-play search index policy and endpoints make it quick and easy to set up and start experimenting.
  • Customizable: A highly customizable indexing policy gives your team complete control over how indexes are created and structured with Elasticsearch.
  • Versatile: Search includes a wide range of options, including custom fuzziness, hard filters, sorting, and text suggestions.
  • Fast: The Search tool pre-processes everything that returns, and processing is done ahead of time so your search results return almost instantly.

Learn more about Search: Understanding the Basics of GraphGrid Search

Enhance Your Artificial Intelligence

Building on all of the above, GraphGrid delivers connected context for knowledge graph-driven artificial intelligence.

Knowledge graphs are the foundation of modern graph data science and machine learning. By delivering knowledge graphs on a graph database – and therefore ensuring no impedance mismatch – GraphGrid ensures that both humans and their AI capture the same image of the world through data. The result is improved bi-directional understanding and accessibility.

Natural Language Processing (NLP)

Natural Language Processing (NLP) makes possible the rich and contextual knowledge graphs your organization needs for mission-critical AI. Using NLP, your developers can turn documents, social media posts, news feeds, and other text into a graph of connected data.

In addition, continuous processing capabilities ensure that your knowledge graph is always up -to date by automatically ingesting new data sources. As a result, your team gets real-time insights based on real-time data.

The Natural Language Processing capabilities also includes the following features:

  • Transforming text documents into graph datasets
  • Similarity scoring between documents using TF-IDF and other methods
  • Relationship extraction to identify how people, places, and things are interconnected
  • Keyphrase extraction that pinpoints concepts associated with particular nodes
  • Named Entity Recognition (NER), that identify people, locations, and organizations

When your AI – and your development team – understand natural human language at this level of detail, they make better decisions that drive your organization forward.

Conclusion

It’s time to stop just collecting data and start connecting it. This paradigm shift ensures no data point goes to waste: every connection provides new value and insight.

By using GraphGrid, you bring together all of the data capabilities of your enterprise organization and multiply your return on connected data. Your development team, your data analysts, and your AI can all work hand-in-hand to advance the mission of your organization. It’s time to get them connected.

Ready to connect your data?

Get started with GraphGrid today or download GraphGrid and take it for a spin.