June 2023 Summaries

Metaplane is planning to support Snowflake's upcoming Data Metric Functions, which aim to automate the recording and centralization of measurements on tables within a data warehouse. The integration will leverage predefined data quality metrics out-of-the-box and provide enhanced performance and accuracy for Metaplane checks. This collaboration between Metaplane and Snowflake is expected to empower data teams with comprehensive data observability solutions, driving meaningful outcomes for Snowflake customers.

Metaplane has achieved Snowflake Premier Partner status, becoming the first Data Observability tool to pass the Technical Validation process. This designation is awarded to organizations with exceptional expertise in utilizing Snowflake's cloud data platform. Metaplane underwent rigorous training and certification processes, allowing them to provide customized solutions tailored to clients' specific data and analytics needs. The partnership aims to improve data quality for customers using Snowflake, including Car & Classic, Appcues, Reforge, SpotOn, Vendr, and Mux. Metaplane is currently working on a new feature with Snowflake that will be announced after the Snowflake Summit.

Metaplane has introduced an upgraded monitoring platform with a redesigned monitor page, more predictable alert behavior, and increased visibility into underlying data for Snowflake customers. The new features aim to improve the user experience by filtering out noise, streamlining workflows, and adding useful context. Changes include a redesigned graph with contextual axes, additional table context, an overview section displaying high-level information about the monitor, and streamlined configuration options. Furthermore, Metaplane has made improvements to alert behavior by aligning the expected range on the graph with the range that triggers an alert. For Snowflake users, Metaplane now captures snapshots of freshness and row count for every table or view in their database, allowing them to investigate any issues without additional costs. The update also includes a rewrite of how monitoring is performed, resulting in faster page loads with fewer errors and accelerated development speed for new monitor types and capabilities.

Data observability is the degree of visibility into your data at any point in time, including monitoring, troubleshooting, and ensuring data quality throughout the data stack. It plays a critical role in ensuring that data is available, accurate, and trustworthy by addressing common issues such as data inconsistency, outdated or incorrect data, and data silos. The four pillars of data observability are metrics, metadata, lineage, and logs. Data observability tools can help detect anomalies, implement a robust data CI/CD pipeline, visualize data lineage, and provide insight into how your data is being used. Some popular data observability tools include Metaplane, Monte Carlo, and Datafold.