In Data We Trust

The data observability tools ecosystem is relatively new—and evolving quickly. Read on to learn what these tools do, and how to evaluate which data observability platform suits your team in 2025.

Learn what the MERGE statement does Snowflake, as well as examples and best practices om when to use it.

Explore how ensuring data validity can strengthen your data quality strategy and drive actionable insights.

Data quality versus data observability isn't a debate. These two concepts work together—one as the goal and one as the means. Discover the nuances of both in this article.

Data anomalies can be a result of natural causes, or they could mean that something in your pipeline is seriously broken. Read on to learn all about data anomalies, how they impact your pipeline, and tips for finding and resolving them.

Welcome to ‍—a monthly roundup of news you can use from around the data world.

Learn how Metaplane's purpose-built ML model differs from other data observability tools, and the difference that means for customers.

Data accuracy is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.

NVL and IFNULL in Snowflake function very similarly—with some subtle differences. Read on to learn how they're similar, how they're different, and when to use each one.

Deploying monitors with Metaplane is as easy as it gets—but there's still a few best practices to keep in mind as you roll them out. We'll walk you through each one of them in this article.

Learn how to get the most out of your Metaplane alerts to make your data observability experience even better.

Data quality is essential for success. Learn its importance, challenges, and practices to maintain high standards in your organization.

Data quality is becoming more important than ever, and it's important to have the right tools in your stack to keep up. Here's a list of the top data quality tools for your team in 2025.

Optimizing your Snowflake queries can go a long way in maximizing performance—not to mention reducing your costs. Here are some practical tips on how to write more efficient queries in Snowflake.

Data consistency is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.

Data freshness is one of the ten dimensions of data quality. In this post, you'll learn what it means, why it matters, and how it's measured.

Snowflake costs can creep up in tons of different ways. The good news? That means there's lots of ways to reduce your Snowflake cost, too. Here are ten ways you can bring down your costs in Snowflake.

New in Metaplane: see your monitoring coverage percentage at a glance, spot gaps in critical tables, and add missing monitors with one click.

Welcome to Overheard in data—a monthly roundup of news you can use from inside the data world.

There's no one-size-fits-all solution for handling NULL values—it all depends on context and what you're trying to do. With that in mind, here are five ways of working with NULL values in SQL that should solve almost all of your use cases with ease.

Improving data quality sounds like a huge, never-ending task, but it's important to remember that there is no end destination. Here are eight things your team can do right now to improve data quality.

Let's go over eight of the most common data quality issues that teams face, how you can spot those issues, and what you should do when you have them.

Learn all about how to use the COALESCE function in Snowflake, when you might use it, and how it compares to other NULL-handling functions.

Let's dive into the hype behind Apache Iceberg and break down what it is, why data teams are using it, and whether or not you should too.

New source-to-target monitoring capabilities, dashboards now refresh, and other quality-of-life updates.

Are you a dbt Core user who's struggling to find a good way to host and share your dbc docs? Well, this post if for you. Follow these step-by-step instructions to share your dbt documentation via GitHub, Netlify, or AWS—whichever fits better into your workflow.

Learn how to use dbt macros to write smarter, reusable SQL that's easy to maintain.

Learn how to use the DATEDIFF function in Snowflake, and see some examples of it in action.

dbt-expectations is a dbt package that brings the power of Great Expectations-style assertions to your dbt workflows. Learn about how best to use it.

Today, we're introducing Metaplane dashboards: customizable views that let every team see exactly what they need to see.

Getting too many alerts is, functionally, the same as getting no alerts. Learn how to tame your dbt alerts and make them meaningful for you and your team.

Here's everything you need to know about dbt tests, including what they are, how to write them, and best practices for implementing them in your data workflow.

Understanding the different types of dbt tests can be confusing. We break it all down in this post, telling you the different types of dbt tests, what they do, and when/how to use them.

2024 was a year to remember for the Metaplane team. Join us as we look back at some of our favorite and most impactful features we shipped in 2024, and peek at what’s coming next

Improved seasonality detection, custom bounds, and better handling of zero and negative values for more accurate monitoring.

Metaplane's data CI/CD capabilities now support GitLab repositories.

The sooner you can resolve job failures in dbt, the better. In this article, we'll walk you step-by-step through two different ways to set up alerts in dbt, and tell you why we prefer one method to the other.

Learn all about source-to-target monitors—a new way to ensure that your data stays consistent between your data sources and your target destination.

A how-to on creating our custom dbt Alerting infrastructure.

Track your dbt job performance with our new interactive timeline view.

Metaplane's custom dbt alerting system adds rich context and configurable routing to dbt Cloud notifications, making test failures more actionable while bridging technical and business team needs.

Learn how to use the `DATE_TRUNC` function in Snowflake to round down your dates and timestamps and format your time-related data exactly how you need it.

Learn why data lineage is important in dbt, and how to implement it for better data visualization, easier debugging, and more collaboration.

Several updates to incident management to make your life easier!

Learn all about the IFNULL function in Snowflake, what it does, and when to use it to find and replace null values in your datasets.

Lucas Smith, a data leader at Hudl, helps us demystify the idea of data as a product (and gives some tangible takeaways to try).

Discover how to choose the right table type in Snowflake based on your specific use case and data needs.

Making database schema changes comes with an array of risks—both upstream and downstream. Learn how to mitigate those risks and make your schema changes run smoothly.

The `DATEADD` function can save you a lot of time when working with dates in Snowflake. Here's a quick rundown of how it works, when you'll want to use it, and some best practices to keep in mind.

Metaplane's Snowflake Native App is now available in the Snowflake Marketplace.

Metaplane now supports webhooks for incident events, so you can send incidents where you want, when you want.

Tables are the backbone of your data pipeline. Learn how to create a Snowflake table using a few simple commands.

Learn how giving data a seat at the table has powered the growth of one of the world's most successful fintech companies.

Get the rundown on automated data quality checks—including what they are, what to monitor, and how to set them up.

Data lineage is like a family tree for your data—showing you where it comes from, and how it's related to the rest of the data around it. Learn why data lineage is important and tips to implement it.

Full visibility throughout your dbt pipeline all in one place.

Live time series models can detect anomalies for any metric in your data stack. Here’s how to build one yourself.

Learn how Snowflake provided the technical foundation to turn scalable data observability from a dream into a reality.

Extend observability to your ETL tools by monitoring individual connectors for better control and insights.

Monitor dbt jobs and models independently to dive deeper into root cause analysis and incident resolution.

Explore and automatically identify performance, usage, and cost issues in your warehouse with Data Insights.

Get all your questions answered in one place with our enhanced Data CI/CD feature for streamlined processes.

The Metaplane Chrome Extension shows all users a summary of the metrics you monitor in Metaplane in a convenient side panel.

Discover Metaplane’s newest integration with Airbyte for expanded observability in your data pipelines.

Metaplane now automatically suggests connections you can start monitoring based on query history, service accounts, and through other integrations.

Automate incident workflows by sending data incident events to any 3rd party tool with Metaplane integration.

Prioritize these six can't-miss Snowflake Summit 2024 sessions to stay ahead in the rapidly evolving data landscape.

We’re excited to announce that Snowflake has invested in Metaplane. Here’s how this strengthened partnership will scale us both to new heights.

Here are 3 reasons why you should pair your powerful data warehouse with the leading data observability platform

Our latest feature simplifies high-impact monitoring setup—get started with just a few clicks.

Metaplane’s latest feature offers detailed insights into your warehouse usage—learn how it can benefit your team.

Metaplane now offers expanded support for Databricks, enabling more seamless integration with your stack.

Check out Metaplane’s latest integration with Segment, bringing better data visibility and monitoring options.

Tags in Snowflake are your first step to sound governance. Learn how to use them effectively in your data management strategy.

Metaplane raised $13.8M to scale data trust for businesses. Discover our plans to grow from 100 to 10,000 data-trusting companies.

Boost Snowflake data sampling efficiency with conditional statements that filter unnecessary data, ensuring meaningful results.

Metaplane now integrates with Airflow to bring greater observability and insights into your DAG operations.

Schema drift threatens data accuracy. Learn three ways to track and address schema drift issues in Snowflake effectively.

Adaptive flatline alerts balance detection and false alarms. Learn how to set up timely notifications for data ingestion patterns.

Automatically route data quality incidents to Jira issue tracking with the new Metaplane × Jira integration

Until recently, ML model creation focused more on the architecture of the model itself, rather than the data feeding it. Here's why that's a problem.

Discover the advantages of integrating Census via Metaplane and how it enhances your data operations.

Numeric distribution metrics reveal business patterns. Learn what they are, why they matter, and how to track them in Snowflake.

As Snowflake Data Cloud continues to innovate, we’ll be right there along with them. Discover the advantages of Metaplanein the Snowflake Horizon Partner Ecosystem.

Unlock the benefits of Hightouch integration with Metaplane to enhance data syncs and improve observability.

Learn about our new connection method designed to enhance accessibility and streamline your data workflows.

Follow our best practices for maintaining key aspects of data integrity in your workflows and operations.

Ready to improve data quality to increase trust in your data? Use our experience to avoid common pitfalls!

Confused by new data terms? Discover whether these are new concepts or fresh perspectives on established ideas in this blog.

You can now create custom dashboards in Metaplane to monitor the data health of different segments of your data stack.

Learn how Metaplane and Fivetran can streamline your next warehouse migration with powerful integrations.

Metaplane's latest release for our dbt core integration allows users to avoid unintentional mistakes caused by updates to your models.

Learn more about how Metaplane's new dashboard makes it easier than ever to manage data quality from one place.

Learn how teams across your organization can collaborate to enhance data quality practices and processes.

Read more about Metaplane's latest feature that eliminates the training period for your machine learning based monitors.

A letter about what our latest G2 awards means to me and how Metaplane will use our reviews and feedback to move forward.

Read more about Metaplane's newest feature for Snowflake users who are trying to get the most out of their data stack.

Transactional databases are vital to modern data stacks. Metaplane's integrations ensure they are included in your observability strategy.

Avoid common data quality issues when integrating new tools into your data stack—learn key implementation tips.

Learn about how to use Snowflake Dynamic Tables in conjunction with dbt to accelerate your modeling efforts.