We set up the ownership, catalog, quality controls, lineage and access policies that let people find and trust data, using the governance tools in your platform, including moves from one catalog to another. We start with the data that matters most.
Domains, named owners, descriptions and certification in your data catalog, so people can find the trusted version of a dataset and know who to ask.
An analyst searches the catalog, finds the certified dataset and sees who owns it, instead of picking one of five similar tables.
Automated quality rules and source-to-report lineage that trace a reported figure back to the system it came from.
A quality rule catches a bad batch before the dashboard refreshes and alerts the dataset owner.
Role-based access, sensitivity labels or tags, and audit evidence aligned to your regulatory and internal obligations.
Access to patient or customer data follows job roles, and the evidence for an audit is ready without a scramble.
A register of AI use cases, risk review and named owners, with clear rules on which data each assistant or agent may use.
Before an agent goes live, its data sources, approval boundaries and owner are written down and reviewed.
We work on the platform you have chosen, or help you choose one.
Core datasets are findable, owned, protected and trusted.
Want results fast? This accelerator delivers one outcome in about 30 days.
Most programs draw on more than one service.
Copilots, AI agents and AI features built on your own data and documents.
Lakehouses, warehouses, monitored pipelines and legacy modernization, so data arrives on time.
Dashboards on certified semantic models, so everyone reads the same numbers.
Cloud environments on Azure, AWS or Google Cloud, designed, migrated, secured and run for you, including managed hosting.
Tell us which datasets cause the most confusion, and which catalog or governance tools you use today.
