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Build a competitive advantage using graph data

By Stefan Gerber

Graph data allows organisations to democratise their data landscape. By intuitively modelling data, it becomes accessible, and everyone gets to participate in the conversation.

Most business leaders would agree that information from within their organisation is crucial in guiding their decision-making. They need information to produce actionable insights, and they need it urgently.

Any organization that designs a system will produce a design whose structure is a copy of the organization's communication structure. - Melvin E. Conway

As organisations grow, they subdivide into smaller departments. Within these departments, there is a clear structure of responsibility and a well-defined goal allowing for more efficient and effective work. An obvious benefit is that these divisions can help identify and address weaknesses or areas for improvement within the team while maintaining more personal relationships that lead to greater employee satisfaction.

Unfortunately, there is a price to pay for the benefits that these more focused departments bring.

When the structure of a business subdivides, the sources of information flowing into its decision-making do as well. Separate data silos start to emerge.

Separated data silos describing different organisational departments.

Data silos hide valuable context #

Organically evolving, divided data silos hide valuable context and limit the discovery of insights leaders need to make decisions. Insights that will only become harder to find as our ever-increasingly connected world continues to embrace the cloud and its offerings. Most organisations are, or soon will be, drowning in a sea of data complexity.

However, some have adapted by welcoming data analysts, scientists and engineers to make sense of it all, giving birth to one of the fastest-growing industries in the world. There is no denying the impact these specialities have made, with data science and machine learning models reshaping the world as we know it today.

Even so, for all the benefits that multi-billion parameter models and months of investigative data science provide, they offer limited advantages for business leaders needing urgent actionable insights when their data landscape changes. Identifying trend changes and patterns outside the trained model is limited, if not impossible, due to the rigid nature of the data silos that feed into these models. Without a different approach, it will only become more challenging as data volumes increase. There really shouldn’t be a need to frequently join together tens or hundreds of tables to be able to make informed decisions.

Unlock knowledge and insights using graph #

Graph technologies were built with relationships in mind. They unify data silos and allow businesses to discover complex, deeply nested contexts to make decisions immediately.

Data silos connected by arrows.

But what does all of this mean? How can it help your business? Why should you make changes to a well-understood and very well-established data warehousing solution?

The only justifiable answer would be an immediate, practical benefit. Graph databases achieve this in three primary ways. Simplicity, flexibility and performance.

Simplicity #

When someone asks you to draw or explain the process or model of your organisation, you would go to a board or piece of paper and draw entities connected by relationships with descriptions of these entities and their relationships. A graph.

By continuing to make modern, connected data fit into old tabular technologies, we’ve made it difficult to deal with the clear relationships between them and completely thrown away the ability to discover the hidden ones that connect them in ways we have yet to discover.

Graph data allows an organisation to democratise their data landscape. By intuitively modelling data, it becomes accessible, and everyone gets to participate in the conversation. No other technology enables executives, managers, engineers and customers to understand and reason about the data domain and model in a way as intuitively as graphs do.

Performance #

Real-world data is connected data. When dealing with connected data and comparing relational databases and other NoSQL stores to graph databases, graph databases offer significant performance increases as the dataset grows.

Flexibility #

Markets and business requirements change, sometimes without notice, and organisations need to be able to adapt to these changes and evolve their data model in step with their environment to gain an advantage over their competitors.

Most organisations rely on well-established relational data stores to perform business intelligence and analytics work, using database technology that has remained relatively unchanged for over 40 years. The digital landscape we find ourselves in today has progressed far beyond that.

Modern graph databases have been designed with today's agile methodology in mind. They are naturally additive, which means we can add new kinds of relationships, nodes, labels, and subgraphs to an existing structure without disrupting business processes. This means that organisations can use graph databases as an enhancement above the existing, disconnected data silos.

Can my organisation benefit from a graph data solution? #

The short answer is that most modern businesses that operate at scale will see a benefit from using a graph data solution. The best way to reason about it would be to think about the various departments, products, people and behaviours within your business. If there are clear, consistent interactions between them, it is likely that you do have a large number of relationships within your organisation and can benefit from graph data.

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

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