January 2023 Summaries

Metaplane has released Data Test Previews, a feature that automatically tests any changes made to data in a development branch, allowing busy data teams to find out if they're about to introduce breaking data changes to their environment in minutes rather than hours. This helps incorporate best practices from the software development world and instills confidence when reviewing and merging pull requests. The tool is configurable, allowing users to choose which tests run and fine-tune testing thresholds. Additionally, it enables sharing of data test reports with stakeholders about changes being made and their impact on data quality.

Metaplane introduces an automatic monitoring feature for new tables added to important schemas. Users can enable this by toggling the auto-add test settings on any schema page. This feature includes monitoring of row counts and freshness, ensuring data quality and observability. Additionally, users have the option to choose between UI or code configurations.

Metaplane, an AI-based tool for observing and monitoring data quality, has raised $8.4 million in a funding round led by Khosla Ventures. The company aims to provide full visibility into the state of organizational data, helping companies trust their data. Metaplane's core product continuously monitors metadata and alerts on anomalies, while also supporting issue triaging and remediation through lineage analysis. The funding will be used for product development and growth initiatives, including expanding integrations and refining machine learning models.

Great Expectations is a tool for catching known issues by testing binary criteria on critical tables, while Metaplane is designed to catch unknown issues by testing scalar criteria on a wide range of assets. Both tools have their strengths and can be used in different circumstances. Some customers use both Great Expectations and Metaplane together to achieve comprehensive test coverage across various data sources and types of issues.

dbt tests are designed for catching known issues by testing binary criteria on critical tables, while Metaplane is suited for identifying unknown issues through testing scalar criteria on a wide range of assets. Both tools have their strengths and should be used in the right circumstances. Many customers use both dbt tests and Metaplane together to achieve comprehensive test coverage between binary and scalar outcomes and known and unknown issues.