A Power User’s Experience on Using Graph Databases to Drive Better Decision Making

“Bloom visualization makes it easy to drive discussion and help my clients understand the cheapest, fastest, or the greatest value path available to them and drive better decision making,” said Rob Orlando, Chief Operations Officer, Processus Group.

I recently met with Rob Orlando, an experienced graph database user, and he shared his experience using Neo4j AuraDB Professional tier. Check out our conversation below for a peek into his work with graph technology.

Tell us about yourself.

Rob Orlando (RO): I’m a co-owner and Chief Operations Office of Processes Group. My background is “computer scientist.” It is a bit of a catch-all. I have and continue to consult as a network engineer, systems administrator, data scientist, software engineer, systems engineer, or software developer. For now, my work is to support the Department of Defense (DoD) as a systems engineer and data scientist.

How did you discover Neo4j?

RO: A few years ago, my colleague introduced me to Neo4j – as we were using an analytics tool called Protege – and encouraged me to explore Neo4j. I didn’t think much of it at that point in time, until a year ago we had a project with the army and I remembered Neo4j. I compared both Protege and Neo4j AuraDB Professional and decided to go with Neo4j. The Bloom visualization tool is extremely useful in customer presentation.

Why is Neo4j useful to you?

RO: I have tried using PowerPoint and Excel to demonstrate to my customers the cheapest and fastest paths options, but these presentation formats were challenging because every client needed to see data presented a different way and at different levels of abstraction. So I decided to switch to graphs since they give me a way to quickly generate visualizations based on the scope of the discussion.

I use Neo4j AuraDB to identify the fastest and cheapest options to help clients make better decisions faster. Having an interactive visual presentation made it easier to consume data insights and accelerate the decision making process, often referred to as the OODA loop in DoD.

To learn Neo4j, I watched the training videos on YouTube and read articles on Stack Overflow. I also learned the Cypher language.

When I used graphs to connect different components and demonstrated the impact of a change in one component affects funding and other technical decisions, they were able to follow the discussion better and make an expert decision.

The graph visualization and the ability to use different colors simplified the complex layout and made it easy to engage with customers. I highlight nodes from the high level plan down to individual tasks to quickly determine who needs to take which actions.

This is important. Keith Cunninghan, a well known entrepreneur, said it best: “A good idea you can’t execute is a bad idea.” Clients need to know if their plans can be executed, and Neo4j helps them do that.

Now that I know how to use graphs, it’s getting easier to support multiple clients. The base structure we’ve developed over the past decade has broad applicability, and it allows us to quickly provide value on new projects. Most of the time, I just need to change the custom perspectives and extend them to make it work for the new project.

This is especially important in the DoD where the need to improve multi-domain operations – operations that take place on land, on the sea, in air, in space, and in cyberspace – has become even more critical.

How would you describe Neo4j?

RO: To me, it is a knowledge management system on steroids. It is basically creating a mastermind and building that into a graph that is scalable and isn’t a bunch of hyperlinks. I have the ability to run mathematical equations to derive data-driven and, more importantly, knowledge-driven solutions. It basically allows us to combine near-real-time data with expert knowledge to create situational understanding putting expert knowledge into play.

How can we make your experience better?

RO: Quick answer, a modified cost model. Cost models that work in industry do not always fit one-to-one with DoD.

Note: We encourage Rob to share his feedback here.

What advice would you give users who want to try out AuraDB Free?

RO: This is just my opinion and it is alright to disagree. Always start with an objective. What you are trying to solve and modeled after it. I have worked with data scientists, and they have always started with data. I have encouraged them to think differently. Once you have the objective, understand the steps, dependencies, or building blocks required to meet that objective. Put another way, focus on only the datasets required for that use case, then work on progressively more complicated use cases.

If you tell a potential client you need to clean all their data before they see any return on investment, they’ll most likely decide it’s too complicated of a problem to solve.

Thank you Rob for sharing your thought process and your journey in using AuraDB Professional tier. It’s also always good to know how our users leverage our product to meet their customers’ needs.

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