# Datachecks

## Docs

- [Asset Discovery Agent](https://docs.datachecks.io/agents/asset-discovery.md): Explore your data assets using natural language. The Asset Discovery agent queries your registered schemas and generates SQL on demand.
- [Data Validation Agent](https://docs.datachecks.io/agents/data-validation.md): Describe what you want to validate in plain language and the agent configures the validation for you.
- [Migration Assessment Agent](https://docs.datachecks.io/agents/migration-assessment.md): Analyze stored procedures, views, and SQL complexity in your source database and get a structured migration readiness report.
- [Agents Overview](https://docs.datachecks.io/agents/overview.md): Datachecks uses four AI agents to automate discovery, assessment, validation, and translation across your migration.
- [Translation Agent](https://docs.datachecks.io/agents/translation.md): Automatically translate SQL queries, views, and stored procedures from your source database dialect to your target platform.
- [Email Notifications](https://docs.datachecks.io/alerts/channels/email.md): Configure SMTP email as a notification channel for validation alerts.
- [Slack Notifications](https://docs.datachecks.io/alerts/channels/slack.md): Configure Slack as a notification channel to send validation alerts to your team.
- [Microsoft Teams Notifications](https://docs.datachecks.io/alerts/channels/teams.md): Configure Microsoft Teams as a notification channel to send validation alerts via webhook.
- [Alert Details](https://docs.datachecks.io/alerts/details.md): Inspect the full context of an alert — metrics, anomaly log, and status management.
- [Alert Lifecycle](https://docs.datachecks.io/alerts/lifecycle.md): How alerts move from creation through investigation to resolution in Datachecks.
- [Overview](https://docs.datachecks.io/alerts/overview.md): Monitor and manage alerts triggered by validation threshold violations.
- [Alert Statuses](https://docs.datachecks.io/alerts/statuses.md): Reference for all six alert statuses in Datachecks and what each one means.
- [Create Comparison](https://docs.datachecks.io/api-reference/comparisons/create.md): Create a new comparison between a source and target dataset.
- [Execute Comparison](https://docs.datachecks.io/api-reference/comparisons/execute.md): Submit a comparison for execution. Returns a job ID you can use to monitor progress.
- [Execute Multiple Comparisons](https://docs.datachecks.io/api-reference/comparisons/execute-multiple.md): Execute a batch of comparisons as part of an agent run.
- [List Data Sources](https://docs.datachecks.io/api-reference/data-sources/list.md): List all data sources in the workspace with optional filtering, sorting, and pagination.
- [API Reference](https://docs.datachecks.io/api-reference/introduction.md): REST API for programmatic access to Datachecks.
- [Get Job Details](https://docs.datachecks.io/api-reference/jobs/details.md): Retrieve details for a list of comparison jobs by their job IDs.
- [Get Diff Details](https://docs.datachecks.io/api-reference/jobs/diff-details.md): Get the full row-level diff for a completed comparison job.
- [List Comparison Jobs](https://docs.datachecks.io/api-reference/jobs/list.md): List comparison jobs in the workspace with optional status, dataset, and time range filters.
- [Terminate Job](https://docs.datachecks.io/api-reference/jobs/terminate.md): Terminate a running comparison job by its task ID.
- [Dataset Discovery](https://docs.datachecks.io/assets/dataset-discovery.md): Control which tables are included or excluded when Datachecks scans a connected data source.
- [Overview](https://docs.datachecks.io/assets/overview.md): A centralized hub for exploring and monitoring all datasets connected to your workspace.
- [Profiling](https://docs.datachecks.io/assets/profiling.md): Datachecks profiles your datasets using both statistical and semantic analysis to give you a complete picture of your data before and after migration.
- [Create a Comparison](https://docs.datachecks.io/comparisons/create.md): Step-by-step guide to configuring and running a comparison between two datasets.
- [Comparison Details](https://docs.datachecks.io/comparisons/details.md): Inspect the full results of a comparison run across schema, primary keys, and column values.
- [View Comparisons](https://docs.datachecks.io/comparisons/overview.md): View, filter, and manage all dataset comparisons in your workspace.
- [Alerts Dashboard](https://docs.datachecks.io/dashboards/alerts.md): Monitor incidents, alert volume, and resolution rates across your workspace.
- [Comparisons Dashboard](https://docs.datachecks.io/dashboards/comparisons.md): Monitor comparison job performance, results distribution, and dataset diff metrics over time.
- [Validations Dashboard](https://docs.datachecks.io/dashboards/validations.md): Track schema coverage, validation health, and execution trends across your datasets.
- [Azure SQL](https://docs.datachecks.io/data-sources/azure-sql.md): Connect Azure SQL as a data source in Datachecks.
- [BigQuery](https://docs.datachecks.io/data-sources/bigquery.md): Connect BigQuery as a data source in Datachecks.
- [Databricks](https://docs.datachecks.io/data-sources/databricks.md): Connect Databricks as a data source in Datachecks.
- [MySQL](https://docs.datachecks.io/data-sources/mysql.md): Connect MySQL as a data source in Datachecks.
- [Oracle](https://docs.datachecks.io/data-sources/oracle.md): Connect Oracle as a data source in Datachecks.
- [Overview](https://docs.datachecks.io/data-sources/overview.md): Connect your source and target databases to Datachecks.
- [PostgreSQL](https://docs.datachecks.io/data-sources/postgresql.md): Connect PostgreSQL as a data source in Datachecks.
- [Snowflake](https://docs.datachecks.io/data-sources/snowflake.md): Connect Snowflake as a data source in Datachecks.
- [Sybase](https://docs.datachecks.io/data-sources/sybase.md): Connect Sybase as a data source in Datachecks.
- [Core Concepts](https://docs.datachecks.io/getting-started/core-concepts.md): Key terms and concepts used across the Datachecks platform.
- [Quickstart](https://docs.datachecks.io/getting-started/quickstart.md): Connect a data source and use the Asset Discovery agent to explore your data in minutes.
- [Introduction](https://docs.datachecks.io/index.md): Datachecks is an AI-powered data migration copilot that helps you migrate to cloud platforms faster and with confidence.
- [API Keys](https://docs.datachecks.io/reference/api-keys.md): Create and manage API keys for programmatic access to the Datachecks API.
- [Audit Logs](https://docs.datachecks.io/reference/audit-logs.md): Track all user activity in your workspace for security, compliance, and troubleshooting.
- [Error Codes](https://docs.datachecks.io/reference/error-codes.md): Reference for all error codes returned by the Datachecks platform.
- [Data Generators](https://docs.datachecks.io/reference/functions.md): Reference for all synthetic data generation functions available in Datachecks test data.
- [Jobs](https://docs.datachecks.io/reference/jobs.md): Monitor and manage comparison and validation job executions across your workspace.
- [Masking](https://docs.datachecks.io/reference/masking.md): Hide sensitive column values in the Datachecks UI without modifying your underlying data.
- [Thresholds](https://docs.datachecks.io/reference/thresholds.md): Configure auto or constant thresholds to trigger alerts when a validation metric crosses a boundary.
- [Validation Types](https://docs.datachecks.io/reference/validation-types.md): Full reference for all validation types and their configuration functions in Datachecks.
- [Validation Window](https://docs.datachecks.io/reference/windows.md): Configure global or tumbling time windows to control how validation metrics are calculated.
- [Fabricate](https://docs.datachecks.io/test-data/fabricate.md): Build synthetic datasets from scratch by defining tables and columns with data generators.
- [Test Data](https://docs.datachecks.io/test-data/overview.md): Generate synthetic test data that mirrors your production data patterns or build datasets from scratch.
- [Structural](https://docs.datachecks.io/test-data/structural.md): Generate synthetic test data that replicates the structure and data patterns of an existing datasource.
- [Configure Validations](https://docs.datachecks.io/validation/configure.md): Step-by-step guide to creating and configuring a validation on a dataset.
- [Validation Details](https://docs.datachecks.io/validation/details.md): Inspect metric history, incidents, and run results for an individual validation.
- [Overview](https://docs.datachecks.io/validation/overview.md): Monitor data quality by running checks on your datasets and tracking results over time.
- [Manage Users](https://docs.datachecks.io/workspace/users.md): Invite and manage users in your Datachecks workspace.
- [Manage Workspaces](https://docs.datachecks.io/workspace/workspaces.md): Create and manage workspaces in Datachecks.

## OpenAPI Specs

- [openapi](https://docs.datachecks.io/api-reference/openapi.json)

## Optional

- [About Datachecks](https://www.datachecks.io)
- [Blog](https://www.datachecks.io/blog)