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Assets is the central place to explore and monitor all data sources connected to your workspace. It organizes your connected databases into a three-level hierarchy and surfaces data quality metrics, validation results, and schema details in one view.

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Three-level hierarchy

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Datasources

The top level lists every database connected to your workspace. For each datasource you can see:
  • Name and connection type
  • Status
  • Number of datasets and columns
  • Validation metrics including failed validation count
You can search across datasources, trigger a rescan to pick up schema changes, and view aggregate quality statistics.

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Datasets

Clicking into a datasource shows its datasets (tables and views). For each dataset you can see:
  • Status
  • Column count
  • Number of validations run
  • Domain classification

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Dataset detail

Clicking into a dataset opens the detail view with three tabs: Overview, Validation & Alerts, and Configuration. Overview tab
  • Health score — a quality score broken down across six dimensions: reliability, uniqueness, completeness, distributions, custom checks, and validity
  • Row trends — row count over time
  • Data preview — a sample of rows from the dataset so you can inspect the data directly without leaving Datachecks
Configuration tab Manage dataset-level settings:
  • Description — add or edit a human-readable description for the dataset
  • Domain — assign the dataset to a domain to group related datasets across datasources

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Validations and alerts

The Validation & Alerts tab on a dataset shows all validations applied to it along with any alerts they have triggered. Validations All validation rules for the dataset are listed here. You can:
  • Filter by status, category, method type, threshold type, and collection
  • Enable or disable individual validations
  • Adjust thresholds and configuration without leaving the dataset view
Alerts When a validation detects a threshold violation, an alert is raised. The alerts for this dataset are shown alongside the validations that triggered them, so you can see at a glance which checks are failing and what the current alert state is.

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Column masking

Sensitive or PII columns can be masked within the UI. This is useful in shared workspace environments where not all users should see raw column values. Masking is configured through the Profiling workflow, which identifies sensitive columns automatically.