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How to Build and Manage Your Own Enterprise Knowledge Graph

Learn how GraphGrid Manager lets you build, define, and manage your own enterprise knowledge graph

It’s no secret that the most successful organizations today are using enterprise knowledge graphs to achieve long-term success – whether that’s advancing a particular mission, growing the bottom line, or both.

Enterprise knowledge graphs break down silos, disperse tribal knowledge, and increase collaboration. They’re also the key to retaining institutional expertise long after key employees leave or retire, and they form the foundation of a diverse number of AI/ML projects. But most importantly, enterprise knowledge graphs allow organizations to adapt to an uncertain future by enabling both iterative and bold-step innovation.

All of the above compelling reasons are why knowledge graphs – powered by a native graph database – are at the heart of GraphGrid Connected Data Platform (CDP). With GraphGrid CDP, enterprises can leverage 100% of their data (and not just 10% of it). After all, knowledge is inherently more valuable when it’s connected.

But for many development teams, using graph technology represents a hefty time investment. And while that investment is ultimately worth it in the long run, you don’t have to become a technical graph expert in order to reap the returns of connected data today.

That’s because the GraphGrid Manager makes it easy to build and manage your own enterprise knowledge graph without extensive graph know-how. You could start right now, even.

Design & Define Your Knowledge Graph with GraphGrid Manager

The GraphGrid Manager allows you to design, create, and maintain a knowledge graph model that is specific to your organizational requirements.

With Manager, you’re in control: You can define a custom graph data model that meets your existing and future data requirements. For example, if you’re creating an internal knowledge graph of personnel at your organization, you can map a person and their characteristics in relation to their team, department, regional division, and national-level business unit. You can map people to skills, to projects, to other personnel, to prospects/accounts, or to whatever else your organization needs within the knowledge graph – you decide.

The Manager also lets you curate your own individualized library of node types, relationship (or edge) types, properties, and constraints. You define which node types have what particular properties or which relationship types exist between person nodes and location nodes. The graph schema is entirely in your hands, but it doesn’t require deep graph understanding in order to get started.

GraphGrid Manager also includes Showmes. You can create and control these dynamic APIs using the Geequel graph query language to return targeted result sets of graph-based data. While you do need technical knowledge of Geequel in order to create Showmes, you don’t have to be technical in order to execute them – much like driving a car doesn’t require you to be a mechanic.

When creating a Showme, your developers can associate it with a NodeType to provide your analysts and non-technical users with recommended steps to take during data discovery. Showmes were included in the Manager module to make linking to NodeTypes simple and straightforward for your analyst team.

For example, if you’re looking at a `Person` node and want to know if that person visited one of your stores last week, then your dev team can make that analytical query into a Showme linked to the `Person` NodeType. So when analysts are next looking at your weekly data, they’ll see this Showme and can run it on any target `Person` node they’re interested in.

The best part? As new data is introduced into your knowledge graph, the Showme incorporates those updates into its results in real time. Read my earlier blog post on GraphGrid Showmes for more information.

For a closer look at every feature and capability, check out the GraphGrid Manager documentation.

Maintain Your Knowledge Graph with Manager Models

Another major component of GraphGrid Manager is the ability to create Manager Models.

A Manager Model is a specification for your knowledge graph: It shows which nodes, relationships, and properties can be created in the GraphGrid UI and how they can be structured. Manager Models are also versioned to keep track of previous specifications of your graph.

In addition, a Manager Model is itself a graph and consists of several predefined nodes and relationships. (However, Manager Models are not enforced, as with ONgDB constraints.) The node labels in a Manager Model include:

  • `Manager`
  • `ManagerVersions`
  • `NodeTypes`
  • `EdgeTypes` (i.e., relationship types)
  • `Constraints`
  • `Properties`

Below is a graph visualization of the different nodes and relationships you’ll find in a Manager Model. (Note this diagram doesn’t include the contextual Manager or versioning `ManagerVersion` nodes.)

Graph Visualization

Think of Manager Models as the laws of your knowledge graph that help keep your enterprise data organized and running smoothly – even when you’re not around. Manager Models help you administer your knowledge graph without being a technical expert.

Learn more about Manager Models in the GraphGrid documentation.

Bolster & Enrich Your Knowledge Graph with Context-Aware AI

With GraphGrid Manager, you design and define your knowledge graph, but maintaining an enterprise knowledge graph still takes significant time and effort. Fortunately, the other modules of GraphGrid Connected Data Platform (CDP) help you maintain your knowledge graph over the long run. After all, an enterprise knowledge graph isn’t just a one-time project; it’s an ongoing investment in the future of your data.

Once you’ve defined the specifications of your knowledge graph, context-aware AI in GraphGrid CDP detects where existing and emerging gaps exist in your knowledge graph model and suggests edits. The Natural Language Processing (NLP) service scans your graph and lets you know when you need to add new node or relationship types.

All of these CDP services ensure that you maintain uniform naming for entities and properties within your graph model, without requiring a herculean effort of time and energy. In the end, your knowledge graph remains consistent and up to date for all end-users.

Conclusion

GraphGrid Manager lets you build an enterprise knowledge graph with all the advantages of a native graph database and none of the hefty time sink to become a standalone graph expert. With Manager, you scale easily as your data needs change, you can ensure data consistency across your knowledge graph (and across your organization), and you track how your data changes over time.

But more than all of that, an easy-to-build, easy-to-maintain enterprise knowledge graph allows your organization to innovate in a future-proof way. Because if you have all of your knowledge organized and accessible from a single place, there’s no future you can’t face.

It’s time to get building:
Download GraphGrid CDP and design your own knowledge graph today.