Sharing knowledge is the basis of every business. Companies typically do this by recording everything that happens in a CRM (customer relationship management) system. Still, it’s not easy to make sense of all those notes and updates later on.
That’s where a graph database comes in – it makes an abstract concept practical by removing the clutter and the noise of regular data.
Example Use Case
It’s difficult to understand the “examples use case” concept without a specific example, so here’s one: Let’s say your company makes cars, and is constantly trying to improve its product.
You might decide that having an up-to-date list of all your parts with their attributes is the first step towards that goal. But then, what happens when you want to update or change that model?
You might spend hours or even days updating every piece of information about each of those parts in several different systems (e.g., here’s where they are on the production line; here’s who is responsible for them; here’s how much they cost; etc.)
Instead, you could use a graph database that continuously realizes the relationships between these objects and updates them automatically. Adding a new part would immediately be connected to everything else in the system because it is already linked to its predecessor or successor through a relationship.
This also means that if you change anything about a part, the graph database would automatically propagate those changes to other related parts and other systems. Hence, it is easy for everyone in your company to access and update the data because it’s always available and up-to-date, thanks to these relationships.
As we can see from this example, databases that use graph structures can help you solve a wide range of problems that traditional relational databases cannot.
In the following sections, we’ll go over some common questions about graphs and how you can use them to improve your product lifecycle management.
Question 1: What are Graph Databases?
Graph databases allow you to model, store, and query data that follows the relationships between objects. They work best for highly connected data that often changes, like customer profiles or product information.
You can use a graph database to model a wide range of information in your company. For example, you can use them to track an IT equipment’s replacement cycle by modeling the product life cycle as a graph.
In this case, each node is equipment or part with properties including its start and end dates and the ones linked to through relationships.
Each edge represents an interval of time, so the graph allows you to search for all nodes in a certain period. For example, if you want to determine how long equipment has been used, you can traverse the graph from node to node until the end date appears.
Question 2: Why Use Graphs in Product Lifecycle Management?
Graph databases are best for modeling highly interconnected data that changes often. Because they were designed to handle complex relationships, they provide fast querying capabilities for this type of information.
You can use graphs in product lifecycle management systems to represent complex interrelationships between objects in your company’s database. For example, you could create a graph with all the parts of an IT product as nodes and their relationships as edges.
Each time you change your production system, it will propagate through the graph because every node is visible to everyone who manages it.
You can then use queries across multiple systems to determine how changes in one place affect other objects in your company. Graphs also provide a simple and efficient way of dealing with the complex relationships between objects stored in your system.