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Data governance: lineage, checks and roles
Every number on a dashboard should say where it comes from, which checks it passed and who can change it. In Muvia, lineage from file to dashboard, Data Checks with quarantine, roles and the activity log all live in one place, next to the data.
Illustrative scenario: it describes a typical case, not a customer project.
"Where does this number come from?" should not be a hard question.
A number on a dashboard goes through a file, a cleaning step, a calculation and a widget. When someone challenges it, retracing the path means asking whoever wrote the query, hoping they still work there, and checking by hand which rows were excluded.
Governance is not a separate document: it is lineage computed from the real definitions, checks that leave a trace, roles that say who can change what, and a log that keeps who did it.
- Who it's for
- Data owners and data teams, IT and security, internal control and whoever answers for the numbers to management; the analysts who use them.
In Muvia, step by step
Real product screens, recorded on a project with sample data.
The video · Every number on a dashboard should say where it comes from, which checks it passed and who can change it. In Muvia, lineage from file to dashboard, Data Checks with quarantine, roles and the activity log all live in one place, next to the data.
What you get
- Every number has a path
- Lineage is read from the real definitions, not from a diagram drawn a year ago.
- Exclusions are visible
- What the checks kept out sits in quarantine, with the reason, and the dashboard shows how many rows are valid.
- Who can do what is written down
- Roles separate those who read from those who edit, permission by permission, with no verbal exceptions.
- Changes leave a trace
- The activity log keeps who changed a role or a permission and when, sealed every night.
For the technical team
How it is built in Muvia
- 1
Read the lineage
Each query's Usage tab shows what sits upstream and downstream; the Project Map draws the whole project, from source to dataset to widget to dashboard, always computed from the live definitions.
- 2
Declare the checks
On the validated orders query, write the Data Checks: plausible amount, region present, known customer. Excluded rows go to quarantine with the rule they broke, and whoever manages the data gets a notice.
- 3
Certify what people use
The dataset behind the dashboards has stable fields and is marked as certified: pickers offer it first and Athena prefers it.
- 4
Give everyone their role
Custom roles and permissions, such as an analyst who can read everything and change nothing. Add email codes, TOTP, passkeys and a company-wide MFA policy.
- 5
Keep who did what
Creating a role, changing a permission, a public link: it all goes into the activity log, sealed every night.
- The data it needs
- Online orders in hourly files from an SFTP folder
- Customers and terms from the ERP on SQL Server
- Regions and sales reps from Salesforce
- The quality rules written by the team and the company's roles
More cases in this line
All use cases- Data science on company dataYour data scientist trains wherever they like, in their own Jupyter with their own tools. Muvia gives them governed data to start from, runs the model on a schedule next to the data, and puts the scores into dashboards, alarms and reports.
- Athena: from a question to a query and a notebookOne question in plain language and the work is done: Athena saves the query in the Lab, writes the notebook with the ranking and the conclusion, and explains from the data what happened. Everything stays in the project, can be checked, and is one keystroke away.
- Data from business systems, checked before useFiles, databases and online services connect from one catalogue, and each becomes a table with no schema to design. Before the data reaches a report, written rules keep the bad rows out and set them aside in quarantine with the reason.
Bring us a question you can't answer today.
We start from a real question your business has and walk the path from source to dashboard with your systems, not a demo dataset.