Every issue tracked from detection to closure
Data quality rules and monitoring, data asset catalogue and operations
Data quality is an operating mechanism; a one-off cleanse does not fix next month's problems. We design quality dimensions and rules, run profiling and audits, build monitoring, alerting and a closed-loop issue process, and pair it with asset inventory, catalogue and data service packaging to support asset operations and data-as-asset capitalisation.
Our approach
One team scopes, executes and retests; conclusions are delivered as evidence, not checklists.
Rules are derived from business impact
Fields that affect reports, decisions and external filings are identified first and get rules. A rule library that covers every field produces noise.
Issues have an owner and a closure standard
Each quality issue is assigned to a data owner with a deadline and closure criteria, tracked on the dashboard and escalated automatically when overdue.
The catalogue exists to be used
The catalogue is where data consumers find data. Assets are organised by business domain with definitions, owners, quality scores and a request process.
Deliverables
Quality rule library and monitoring
Quality dimensions, rules, monitoring jobs and alert configuration, with the first profiling report.
Closed-loop process and dashboard
Issue logging, assignment, remediation and closure process with a metrics dashboard.
Asset catalogue and services
Asset inventory, classification and ownership, catalogue portal, data service (API / dataset) packaging standard.
How we deliver
Four stages, each with defined inputs, outputs and a client sign-off.
Profiling and inventory
Profiling of key data, asset inventory, existing issue list.
Rules and catalogue design
Quality rules, closed-loop process, catalogue structure.
Platform go-live
Monitoring jobs, dashboard, catalogue portal and data services.
Operations
Monthly quality report, quarterly asset review, capitalisation support.
Frequently asked questions
Notes on scope, execution and delivery standards. Contact us for anything not covered here.
Completeness, accuracy, consistency, timeliness, uniqueness and validity. Each has executable rules and thresholds, scored by field, table and business domain.
Start from where you stand
Security, data and AI each start with a review of where you stand. The report and its findings are yours, whether or not the engagement continues.