Workspace
A workspace is the top-level organizational unit in Datachecks. All data sources, assets, validations, comparisons, and jobs belong to a workspace. You can create multiple workspaces to separate projects, teams, or environments (for example, staging vs production). Only admin users can manage workspaces and add data sources to them.Data Source
A data source is a database connection registered in your workspace. Datachecks supports Snowflake, Databricks, BigQuery, PostgreSQL, MySQL, Oracle, Azure SQL, and Sybase. You connect a data source once under Settings and then reference it across validations, comparisons, and agent runs.Asset
An asset represents a dataset (table or view) within a data source. When you add a data source to a workspace, Datachecks discovers and registers its datasets as assets. Each asset tracks schema, column metadata, and data profile information. Assets are the primary unit that agents operate on.Validation
A validation is a rule applied to an asset to check data quality or integrity. Examples include null checks, uniqueness checks, range checks, and custom SQL assertions. Validations run on a schedule or on demand. When a validation detects a threshold violation, it triggers an alert.Comparison
A comparison checks whether data in a source dataset matches a target dataset. Comparisons are used during migration to verify that data has been moved accurately. You can compare row counts, column values, and schema structure. A comparison produces a job that runs asynchronously and returns detailed results including differential percentages and row-level diffs.Structural Comparison
A structural comparison checks the schema of a source dataset against a target dataset — column names, data types, nullability, and primary keys — without examining the actual data values.Collection
A collection is a user-defined group of validations. You use collections to organize related validations together for easier monitoring and bulk operations.Job
A job is an asynchronous background task. Running a comparison, an agent analysis, or a batch validation all create jobs. You can monitor job status, view progress, and terminate running jobs from the Jobs view.Agent
An agent is an AI-powered workflow that automates a specific migration task. Datachecks has four agents:- Asset Discovery — Natural language queries about your data schema and assets
- Migration Assessment — Analysis of migration complexity and readiness
- Data Validation — AI-assisted validation configuration
- Translation — SQL query translation between database dialects