Disable and re-enable tests from a Slack alert
Data changes all of the time—sometimes we move data to new locations, or we remove data that is no longer used. In these cases, Metaplane now makes it simple...
Metaplane Performance Improvements
We rebuilt the way we connect and monitor your databases so we can use the least amount of resources and support more types of monitoring over time. You can also now have finer grain control over connection and query settings such as query timeouts and number of concurrent connections.
Search and View the Health of Any Schema, Table, or Column
You can now search and view the health of any schema, table, column, and dbt projects. Check the health of a schema and its tables at a glance. See recent test failures for a table and its columns. Evaluate the test coverage of a column.
Introducing Query Performance Monitoring
Metaplane now seamlessly collects your slowest running queries and includes helpful metadata like the user, role, and time they occurred so you can know which queries to refactor or remove.
Metaplane now supports custom test scheduling so that you can run tests at specific times of the day.
Introducing Snowflake Table and Column Usage Analytics
It’s easier than ever to ETL data, but harder than ever to understand who or what is using this data. Metaplane now monitors table and column level usage analytics for Snowflake customers so you can better understand how critical data is used, what should be tested, and how to prioritize data quality issues.
Keeping Data Quality in Plain View
This week, Kevin had the opportunity to talk with Kelly on the Hashmap on Tap podcast about how Metaplane helps data teams.
Lineage Visualization Is Here!
Metaplane now visualizes your data lineage from warehouse to business intelligence tools. Finally understand how your data is used across your stack, easily find data assets that could be refactored or removed, and dig into how specific data assets are connected with a few clicks.
Data Quality Begins and Ends Outside of the Analytics Team
Sarah Krasnik, Data Engineer at Perpay, writes about how monitoring is important at every point of the stack.
Redshift and dbt Improvements
We now intelligently use different Redshift table metadata to ensure we are referencing accurate metadata without incurring more load on the warehouse. Additionally, we added more resiliency when making requests to the dbt API.
