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Every organisation needs a knowledge graph

By Stefan Gerber

Over time, organically growing departments within large organisations lead to divided sources of truth, data synchronisation issues and replicated master data. In this post, we will look at how knowledge graphs can be used to manage complex data at scale.

Master data consists of information related to connected entities within your organisation's data landscape, for example, users, customers, products, suppliers, departments, geographies, sites, cost centres, and business units. Master data management is the process of managing data over time as organisational structures transform, businesses merge, and business rules change, incorporating new sources of data and supplementing existing data with externally sourced data.

In large organisations, this data is often stored in various locations, resulting in overlap, redundancy, and inconsistent formats and quality. A common example of this would be customer data spread accross various departments (marketing, sales, finance etc.).

visual graph depicting three instances of the same customer but with each instance linked to different unique details of the customer

From reality to resolution #

The task of matching and merging multiple data sources is known as entity resolution. It aims to resolve the question of who is whom or what is what across different data sources.

visual graph depicting one fully described instance of a customer connected to all of their details

Some additional industry use cases for knowledge graphs include enhanced information searches using powerful graph traversal queries, impact analysis and root cause analysis, and a single view of X, for example, a customer360 view.

The benefits of a connected view within your organisation cannot be understated. It allows information to flow more efficiently, improving the effectiveness of your employees and the experiences of your customers.

Cut the red tape #

Consider an organisation that sells bookkeeping software. It has three primary departments: engineering & support, sales & marketing, finance & legal, and, of course, serves customers. Below is an example of a subset of data that may be available within each department.

Four squares, three of which depict departments within an organisation (Engineering, Marketing and Finance) and the information available within them, and the fourth depicting customers and their available information

None of the departments, with the exception of sales, communicate directly with end users. However, all of them do have their view of a customer's needs and behaviour.

A knowledge graph allows organisations to bridge these fractured sources of truth by creating a consolidated view across the business’s data landscape.

The goal here is to share valuable, non-sensitive information company-wide.

For instance, by allowing engineers to have access to (non-sensitive, i.e. anonymised) sales data, they’ll be able to get a pulse on which features users buying the product are now using. Additionally, engineers can work with the responsible sales agent to set up meetings with specific customers to inquire further about their thoughts on certain features. This can reduce the time it takes to receive and iterate upon customer feedback.

A visual graph connecting nodes representing engineering, sales,customers and features. The relationships between them depict value delivered by the builder, seller and buyer of the features respectively.

Another benefit of a central source of truth would be giving live sales feed data to the marketing team. By getting a live view of data, marketers will be able to launch targeted promotions and see results immediately. The marketing department can also be given access to an ad resource pool indicating the budgets they have available without the need to go through senior management first and allowing them to become proactive in their work.

A visual graph connecting nodes representing marketing, sales and finance departments and data being shared between them.

I hope these examples encourage you to examine your organisation's structures and approach to knowledge sharing. Improving access and visibility to non-sensitive information can create significant value throughout the business.

Conclusion #

Knowledge graphs, master data management, and entity resolution all stem from the ability to connect disconnected systems and processes into one consolidated source of truth, providing benefits to all stakeholders. The whole is greater than the sum of its parts.

At Rockup, we believe in the power of relationships. If your company can benefit from a deeper understanding of the data that drives your success, contact us to schedule a call.

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