Is a Knowledge Graph an interoperable solution for you?

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Before deciding to implement a Knowledge Graph, it is important to do an assessment of what problem you are trying to solve and determine if a knowledge graph is the right solution.

There is no one-size-fits-all recipe. Each data challenge is unique, but we provide you here some guidelines to help you get started.

Identify the Problem

The first step in deciding whether you need a knowledge graph is to identify the problem you are trying to solve.
Ask yourself:
“What kind of information do you need to store?”
“Is it unstructured or structured?”
“Does it have relationships between different pieces of data?”

Understand the Benefits

Once you have identified the problem, it is important to understand the benefits of a Knowledge Graph. A Knowledge graph can help you store and organise large amounts of data, allowing you to make connections between different pieces of data.

It can also provide the ability to:

  1. Improve Data Discovery: A Knowledge graph can help you discover relationships between different entities that were previously unknown. This can lead to new insights about your data and help you make better decisions.
  2. Enable Data Access: A Knowledge graph makes it easier to access and use data by providing a visual representation of the relationships between different entities. This can help you quickly find the data you need and make it easier to use.
  3. Increased Efficiency: By using a Knowledge graph, you can reduce the amount of time it takes to find and use data by eliminating the need to manually search for the data you need.
  4. Improve Data Quality: A Knowledge graph can help improve data quality by providing a consistent structure for the data and ensuring that it is up-to-date.
  5. Improve Decision Making: You can make better decisions about your data by being able to quickly identify relationships and trends.

Assess the Cost

Even if Knowledge graph implementation is becoming cheaper due to the growing adoption, it is important to consider all the costs. For example, we can reduce the costs of starting a data integration project by using a standard RDF Enterprise Knowledge Graph.

Hybrid deployment to meet your business needs

The Knowledge Graph implementation does not follow an identical methodology from one enterprise to another. Many parameters must be taken into account for the success of such a project.

Inspired by our experience in a wide range of contexts, both in terms of the business sector, size and corporate culture, we aim to develop systems that are customised to your business cases and individual needs.

We are known for our flexibility and tailoring and are committed to delivering dedicated experiences that enhance the work of all data stakeholders.

We have extensive experience in designing and implementing Enterprise Knowledge Graphs in government and other data-intensive sectors. Our team of technical experts, industry practitioners, and open and linked data experts can help you see data challenges from a different perspective. We offer hybrid deployments that allow organizations to incrementally explore and evaluate how an EKG can solve specific business challenges.

We help you evaluate how a Knowledge Graph can solve your data challenges. Our team of experts can work with you to identify the best deployment strategy for your organisation, and develop a customised plan to ensure your Knowledge graph is optimised to meet your specific business needs.

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