PRODUCT
Data quality, end-to-end.
NeptunoDQ covers the full cycle: define rules as a team, review them with traceability, and deploy to Apache Spark or Databricks without switching platforms.
From functional analyst to data engine, no friction.
INTRO
Intro
First contact with NeptunoDQ: server startup, navigation, and a global view of the platform.
- Initial server setup
USERS & ROLES
Users & roles
RBAC built for audit: groups, roles, and granular permissions across the platform.
- Users, roles & groups
PROPOSALS
Proposals
The lifecycle that channels every rule change into a trackable, reviewable proposal.
- Proposals
INVENTORY RULES & KANBAN
Inventory rules & Kanban
The functional analyst's daily work: explore the inventory, kanban flow, and create, configure, review or hotfix rules.
- Inventory
- Kanban
- Create a rule
- Configure SQL_TEXT
- Review process
- Hotfix
DEPLOYMENT
Deployment
Pushing the same rules to production on Apache Spark or Databricks — one definition, two engines.
- Databricks deployment
EXECUTION FROM DATABRICKS
Execution from Databricks
Launch a NeptunoDQ run end-to-end from a Databricks cluster: parameters, live execution, and the audit trail back in the platform.
- Execution from Databricks
Better seen in video.
Walk through NeptunoDQ's capabilities with the product demos.