DATAshaper provides a modular foundation to shape, validate, govern, and prepare data across its full lifecycle. Explore the core capabilities that help organisations work faster, reduce risk, and turn data into a reliable asset.
Poor data quality is one of the main reasons data initiatives slow down, cost more than expected, and lose user trust. DATAshaper helps organisations address this early and structurally by making data quality a shared, manageable responsibility rather than a last-minute clean-up exercise.
With DATAshaper, organisations define what high-quality data means in a business context. This includes completeness, consistency, and correctness across customers, suppliers, products, and transactions. As data is processed, DATAshaper continuously checks it against these expectations and highlights where attention is needed.
Issues are clearly prioritised based on business impact. Blocking issues prevent unreliable data from moving forward, while improvement opportunities highlight where quality can be raised without delaying operations. The right people are informed at the right time, enabling fast decisions and focused corrections.
This approach reduces rework, shortens testing cycles, and increases confidence at go-live. More importantly, it creates data that can be safely reused for reporting, automation, and advanced analytics. High-quality, well-structured data is also a prerequisite for successful AI initiatives, as it ensures models and insights are built on reliable foundations.
As data landscapes grow more complex, organisations need clarity around who owns their data, how it is used, and where it flows. Without this, compliance becomes reactive and risk increases as systems, teams, and regulations evolve.
DATAshaper brings structure and transparency to data governance by making responsibilities, data flows, and decisions visible and understandable. It helps organisations define ownership, apply consistent controls, and track how data moves across systems and processes. This creates a clear foundation for compliance, security, and informed decision-making.
By embedding governance into daily data operations, DATAshaper reduces uncertainty and manual oversight. Teams gain confidence that data is handled correctly, audits become easier to manage, and compliance is supported as an ongoing process. The result is better control today and a data landscape that can scale safely with future requirements.
Analytics and AI only deliver value when the underlying data is reliable and well structured. Inconsistent definitions, missing context, or poor data quality quickly undermine trust in reports and advanced use cases.
DATAshaper prepares data so it can be confidently reused across reporting, analytics, and AI initiatives. It supports proven data best practices such as incremental processing, controlled historical tracking, and consistent data modelling, ensuring data remains accurate, traceable, and efficient as it evolves.
By enforcing clear structures, consistent definitions, and validated relationships, DATAshaper reduces rework, speeds up insight, and enables analytics and AI initiatives to scale on trusted data rather than assumptions.
Data migration is one of the most critical and risk-prone moments in any system change. When data is moved without structure or clarity, delays, rework, and loss of confidence quickly follow.
DATAshaper helps organisations approach migrations in a controlled and predictable way. It brings structure to how data is prepared, transformed, and validated, ensuring that business expectations are clear long before go-live. Data issues are identified early, responsibilities are visible, and progress is transparent across teams.
This reduces last-minute surprises, shortens testing cycles, and lowers the risk of costly corrections after launch. At the same time, data is shaped in a way that supports future reuse, allowing organisations to move forward with systems that are reliable and ready for what comes next.
When core business data is created and maintained across multiple systems, inconsistencies quickly appear. Different versions of customers, suppliers, or products lead to confusion, inefficiencies, and loss of trust in downstream processes.
DATAshaper helps organisations establish a single, reliable view of their core data. By aligning information across systems and resolving conflicts, it supports the creation of trusted master records that serve as a common reference throughout the organisation. This enables teams to work with a consistent 360° view of key entities and reduces friction between departments and applications.
With clear standards and controlled data updates, master data remains dependable over time. This strengthens daily operations, improves reporting, and provides a stable foundation for analytics, automation, and AI-driven initiatives that rely on consistent definitions and accurate relationships.
DATAshaper is supported by a network of experienced data professionals from trusted partners. These experts bring deep knowledge of data management, ERP landscapes, and real-world business processes. They work closely with client teams to ensure DATAshaper is applied effectively and delivers tangible results.
Support goes beyond implementation. Partners are committed to helping organisations succeed over time by sharing best practices, guiding decision-making, and supporting adoption as data needs evolve. This combination of a strong platform and dedicated expertise ensures DATAshaper creates lasting value.
We’re just getting started.
DATAshaper was born from real-world lessons and it’s evolving fast.
After building the foundation for flexible, high-quality migrations, we’re now pushing the limits of what’s possible: from AI-driven mapping to automated data correction.
Curious about what’s next? Let’s connect and talk about the future of data migration.
