Incremental roll-out, incremental benefit
The Datasynthesis Platform was designed with the constraints of your existing legacy data architecture in mind. The Platform has been explicitly designed to enable an incremental implementation, avoiding the risks of a big bang approach required by many legacy data management tools. Data validation and transformation rules can be brought under centralized control on a system-by-system, department-by-department basis, allowing immediate business benefit and ROI to be assessed before expanding usage further.
A non-invasive approach
Move your rules, not your data
Moving to a modern data architecture does not have to mean moving your operational data stores. Many operational systems are strongly coupled to their underlying data storage, so however desirable a completely centralized technology architecture may be, typically such an approach is not possible. Rather than having to move operational data, the Datasynthesis Platform has been designed to decouple data rules (data-about-data) from target data stores, meaning that operational proceses and data are left in place to minimise disruption and accelerate implementation.
Low infrastructure footprint
Data quality as a service
The cloud-native design of the Datasynthesis Platform means that no on-premise hardware needs commissioning before implementation. This Data as a Service approach combines rapid implementation without the need for upfront capital expenditure on hardware, further reducing project risk.
Decommission your expenditure
Remove complexity and cost
As data rules are incrementally centralized within the Datasynthesis Platform, legacy data tools can be decommissioned to simplify data architecture, reduce licensing fees and related maitenance costs and resourcing.
Please contact us if you would like to discuss how to migrate from the complexity of legacy data tools to incrementally deploying a modern data architecture.