DATA
Build the foundations to get more from your data and AI
Your data and AI ambitions are only as strong as the platform behind them.
Data engineering solutions, services and consultancy
Valcon’s data engineering services help you build scalable, reliable platforms that get data where it needs to before analytics and AI. Using proven architectures and automation, we reduce engineering overhead and help your teams turn raw data into insight, products and business value more quickly.
Talk to our data engineering consultants
Whatever your challenge, our specialists can help you find a clear way forward. Talk to us about what you want to achieve and how we can help make it happen.
Partner
Micha van der Ende
Director of Data Engineering
Tim Ellens
29%
Only 29% of technology leaders strongly agree their enterprise data meets the quality, accessibility and security standards needed to scale generative AI effectively. Source: IBM Institute for Business Value
DATA PLATFORM
When your data platform becomes the bottleneck
Data teams should be building new products and insights, not constantly rebuilding pipelines and fixing infrastructure.
But fragmented systems, poor data quality and manual engineering can make straightforward use cases slow to deliver. And as demand for AI grows, those limitations become more visible.
We help you create an engineering foundation that removes repetitive work, simplifies delivery and gives your teams a faster route from data to production.
Engineering platforms built for data and AI
Design around what you need
We design a modular Data & AI platform around your existing technology and business requirements. Rather than a one-size-fits-all platform, our data engineering consultancy helps you select the components you need and integrate them with what already works.
Automate the foundations
Using infrastructure as code, reference architectures and reusable accelerators, we automate platform provisioning and deployment. Standardised components reduce repeated engineering work and technical debt, helping you establish production-ready foundations in days or weeks rather than starting from scratch each time.
Accelerate data delivery
Our data engineering solutions standardise how data is ingested, transformed, tested and made available. Metadata-driven frameworks and automated quality checks reduce manual effort and give engineers more time to focus on building valuable data products, analytics and AI use cases.
Engineer for production from the start
We design the platform to perform reliably as your needs grow, supporting everything from data products and analytics to machine learning and AI. Standardised engineering and automated pipelines help you move new data and AI solutions into production faster and scale them across your organisation.
What success looks like
Our Data engineering solutions, services and consultancy helps you:
Reduce time
Reduce platform setup from months to days or weeks
Focus on value
Give engineers more time to focus on higher-value work
Reliability
Improve the reliability and quality of data products
AI Delivery
Scale data and AI delivery across multiple teams
Automation
Reduce technical debt through standardised architecture and automation
Production-ready
Create a production-ready foundation for analytics, machine learning and AI
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Case Study
Keeping critical Mendix applications secure, stable and business-ready
Situation A leading provider of fuel distribution services needed reliable ongoing support for its Mendix application landscape after the initial development phase. Once the applications were live, the client needed a consistent way to manage periodic updates, user requests, monitoring and bug fixes. Without active support, issues could disrupt production workflows, slow down users and…
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Case Study
Using a cloud platform to accelerate AI and data product delivery in construction
Situation A leading European construction and civil engineering company had ambitions to become more data driven and be able to scale the creation of data and AI products. But building the required data infrastructure and platform manually was not a viable option. The scale of the company’s ambition meant they needed a more better way…
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Case Study
Faster project delivery and stronger forecasting for a leading energy infrastructure provider
Situation A leading provider of Denmark’s electricity and gas transmission was dealing with rapid growth and greater complexity in its external environment. Its technology infrastructure was growing rapidly to deal with these challenges, but its project execution capability was limited and not growing at the same rate. As a result, these pressures were exposing issues…
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Case Study
Improving delivery control for major railway renewal projects
Situation A leading provider of railway infrastructure management was responsible for complex railway renewal projects. It needed to improve control over the projects that were running late and were over budget, due to problems with project delivery. Teams needed a systematic way to track progress and spend, understand where any work was being blocked and…
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Case Study
Creating programme visibility during a large-scale banking separation
Situation A leading provider of financial services and customer credit products in the UK retail sector needed to build its own banking capability while migrating customers away from its parent bank within a fixed timeframe. The separation involved multiple stakeholders, third parties and interdependent workstreams, creating the need for greater programme control, stronger governance and…
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Case Study
Building a product-centric data, analytics and AI operating model in the defence industry
Situation A leading defence organisation’s technology function was not delivering the expected business value. Inconsistent processes, inefficient delivery and embryonic data, analytics and AI maturity were creating complexity and limiting the organisation’s ability to function as effectively as it might. The company needed a product-centric operating model for data, analytics and AI that could reduce…
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Case Study
Building a scalable data platform for BI, data science and AI use cases in the construction industry
Situation Our client, a leading European construction company, had several classic data warehouses to house its data. But this set up was limiting its ability to share data and scale new use cases across the organisation. To become more data driven, the business needed a platform that could support its existing reporting requirements, while creating…
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Case Study
Building a clear data roadmap for governance and security in the heating engineering industry
Situation A leading provider of heating and hot water solutions needed a clearer view of how its data could support its business goals and also needed help to make better use of its new data platform. The company lacked a clear vision and strategy for its data. It needed to define how it wanted to…
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Case Study
Building trusted product data to reduce regulatory risk and improve sales visibility
Situation A leading provider of assistive products and solutions for mobility, patient handling and daily living needed stronger control of its product data as the sector’s regulatory demands increased. Due to fragmented systems and data repositories, the company did not have a clear view of where the relevant data was held across systems and subsidiaries…
WHY VALCON
Why organisations choose Valcon
At Valcon, we combine deep data engineering services with proven accelerators and experience delivering enterprise Data & AI platforms.
Our modular, cloud-agnostic approach works with your existing environment rather than replacing it unnecessarily. We bring together architecture, engineering, automation and AI expertise to build platforms that work today and can evolve as your data and AI ambitions grow.
Ready to spend less time building foundations?
Whether you’re replacing legacy data warehouses, connecting fragmented environments or preparing to scale AI, we’ll help you create a platform that reduces engineering overhead and gets data and AI use cases into production faster.