This is a new page
Help us improve it with your feedbackAutomated checks to improve data quality
Keep your data accurate, up-to-date, and consistent, reducing errors and saving you time and money.
About
Manual checks can be slow, unreliable, and lead to outdated or incorrect service information. By using compliant data, you can build automated tools that continuously check for issues, verify updates, and notify data owners.
This makes the information people rely on to find services more accurate and reliable.
These automated checks can:
- Remind service owners to verify and complete their information
- Remove duplicate entries to keep your data clean
- Check for recent updates to make sure all information is current
- Identify extra fields that have been populated that enhance the data (such as costs, schedules, languages)
- Monitor live feeds to make sure they comply with ORUK standards
- Use machine learning to automatically spot discrepancies and changes in the data
Benefits
- Provides an objective way to assess how suitable and reliable a data feed is
- Automates tasks like checking for duplicates and missing information to reduce workload
- Reduces errors and integration costs by making sure data is consistent
Outcomes
- Better quality, more reliable data
- Consistent information across all systems
- Continuous data improvement
- People can reliably find the right services at the right time
Examples
ORUK scheduled validator
Use this tool to automatically check if a data feed meets the required data standard. This ensures the data is always well structured, accurate, and ready to be used by various applications.
WellAware and data assurance
WellAware automatically excludes services not assured in the last three months from search results. This means their directory only shows current and reliable information.
Get started
If this use case is relevant to your organisation, see
a quick step by step guide to adopt ORUK.