DATAshaper is designed around a simple idea:
the right tool, structure, and support at every stage of your data initiatives.
It combines modular tooling, clear organisation, and collaboration support to help teams work with data in a controlled and scalable way.
Working with data requires different perspectives at different moments. DATAshaper provides multiple, connected interfaces so each role can work in the way that suits them best.
Core platform
The central web application where data structures, rules, workflows, and governance are configured. This is where data initiatives are set up and controlled across systems and environments.
Studio & Excel add-in
A familiar and accessible way to interact with data. Teams can review records, identify issues, apply corrections, and enrich data while staying aligned with central rules and controls.
Power BI dashboards
Clear insight into data flows, quality levels, progress, and outcomes. This helps teams and stakeholders understand what is happening, where attention is needed, and how data evolves over time.
Together, these tools ensure that technical teams, business users, and decision-makers can all engage with data without friction.
DATAshaper brings structure to complex data landscapes by organising data across systems, entities, group codes, and environments. This creates a shared framework that connects data initiatives across applications and domains.
By working within this structure, organisations gain a clear overview of their data landscape. Relationships between systems become visible, data responsibilities are easier to manage, and initiatives that once felt isolated start to reinforce each other.
This foundation is essential for scaling data efforts beyond individual projects.
Data initiatives succeed or fail based on collaboration. DATAshaper supports cross-team work by making responsibilities explicit and collaboration manageable.
Roles can be defined, ownership assigned, and access controlled without unnecessary complexity. Business, IT, and data teams can work together within the same framework, each focusing on their responsibilities while staying aligned.
No tool replaces project management, but the right tool removes friction. DATAshaper helps teams stay on the same page, reduces miscommunication, and supports a more structured way of working with data.
DATAshaper connects to a wide range of business systems and data sources. This allows organisations to work across ERP, CRM, and other operational platforms without changing how those systems are used.
In addition, DATAshaper integrates with external services and APIs to support data validation and enrichment. Examples include checking VAT numbers, validating addresses, or applying custom business-specific checks. New connections are added quickly to support evolving needs.
This connectivity ensures data can be validated, enriched, and governed where it matters most.
AI is becoming part of everyday data work. DATAshaper applies AI in a pragmatic way, focusing on areas where it clearly improves speed, accuracy, and understanding.
AI is used to support tasks such as recognising structures, suggesting mappings between systems, identifying patterns in data, and highlighting potential issues. These capabilities are embedded in proven workflows rather than replacing them.
At the same time, DATAshaper helps organisations prepare their data for AI use by establishing clear definitions, improving quality, and harmonising data across systems. This ensures AI initiatives are built on reliable foundations rather than assumptions.
DATAshaper is more than a tool. It is supported by people who care deeply about data and how it creates value in organisations.
Through our expertise and partner network, we work with clients to define structures, workflows, and approaches that fit their organisation. We listen, challenge where needed, and help translate long-term vision into practical steps.
Our commitment is long-term and pragmatic: growing with our customers, learning together, and continuously improving how data is shaped into a trusted asset.
At its core, DATAshaper enables a repeatable and proven way of working with data.
Instead of starting from scratch for every initiative, teams follow a clear and structured pattern that brings consistency and confidence.
Data is systematically ingested, mapped, filtered, deduplicated, transformed, validated, enriched, and loaded. This approach is deliberately simple, yet flexible enough to support a wide range of use cases.
Because the same pattern applies across different contexts, organisations can reuse knowledge and setup across projects. Whether the goal is an ERP migration, building a data warehouse, improving data quality, or preparing data for analytics and AI, the underlying way of working remains familiar and predictable.
This repeatable approach scales naturally. It works for focused projects and grows with more complex landscapes because DATAshaper is designed with scope and simplicity in mind.
Looking for the right solution to support your data initiatives?
DATAshaper adapts to how you work, with expert support available to complement your team where needed.
