Episode 37: Data integration tools
- Embedded IT
- May 5, 2025
- 2 min read
Updated: Jan 16
Data integration sits near the end of the wider data journey. Once data has been collected, stored, governed, analysed, and visualised, organisations face a final challenge: making their systems talk to each other. This is where data integration tools come in.
This builds on our explanation of what data is and how it’s used across organisations.
What data integration really means
Most organisations run multiple systems, each holding its own set of data. HR platforms store employee information, finance systems hold budgeting and spend data, and visualisation tools present information in digestible formats. Data integration tools act as the bridge between these systems so that each application can access the information it needs.
For example, if an HR system wants to know the remaining salary budget for the month, it sends a request to the integration layer. That tool then queries the finance system and returns the answer. This simple concept is the core of data integration.
There is no need to get into technical frameworks or architectural detail. The main point is that integration tools allow applications to share data in a structured, controlled way that supports informed decision making.
Key considerations for technology procurement
From a procurement perspective, data integration tools are usually straightforward software licences. The challenge is not the concept, but ensuring the tool can connect to every system it needs to integrate with.
The most important questions include:
What interfaces does the integration tool support?
Does it connect to systems like SAP, HR platforms, or data visualisation tools?
Are the integration requirements clearly understood, communicated, and contractually committed by the supplier?
The cost of integration rarely ends with the licence. Professional services are often needed to build and configure the interfaces, which can become a significant part of the overall spend. If pricing is based on the number of integrations or transactions, costs can escalate quickly.
Vendor landscape for integration tools
The market includes well-established vendors and a growing number of open source options. Larger technology providers often lead in this space because they already manage databases and enterprise systems.
Examples mentioned include:
Apache data orchestration tools
IBM’s integration suite (traditionally including MQ Series)
Oracle Fusion tools
MuleSoft, known for specialising in integration
Each has its strengths, but the right choice depends on organisational systems, existing architecture, and long-term plans.
Preparing for the future of integration
As artificial intelligence becomes more embedded in everyday operations, organisations will increasingly integrate internal systems with external services. This makes data structure, interface clarity, and a strong integration strategy more important than ever.
A solid integration layer will help ensure that future technologies, including AI tools, can access clean and reliable data.
Final takeaway
At its heart, data integration is simply software that connects systems, moves information between them, and supports cross-application decision making. With the right interfaces and clear requirements, organisations can build an integration layer that scales with their needs.
For organisations looking to strengthen their approach to data and system integration, get in touch.
