In Data We Trust

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

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.

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).

Learn more about how to determine which table type to use in Snowflake based on your use case.

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.

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 further into your ETL tool by monitoring individual connectors.

Monitor dbt jobs and models independently for more root cause analysis.

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

Get answers to all your questions on one page with our Data CI/CD enhancement.

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

Learn more about Metaplane's newest integration with Airbyte.

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

Send data incident events to any 3rd party tool to automate your incident management workflows.

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 helps you setup high impact monitoring in just a few clicks.

Metaplane's latest feature provides deeper insight into how you're using your warehouse.

Metaplane expands support for Databricks

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

Learn more about Metaplane's newest integration with Segment

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 provide observability into your DAG

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.

Learn what you get from integrating Census via Metaplane.

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

Learn what benefits you get from Metaplane’s inclusion in the Snowflake Horizon Partner Ecosystem

Learn what you get from integrating Hightouch with Metaplane.

Learn about our latest connection method

Best practices for maintaining a few aspects of data integrity.

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 about how you can use Metaplane along with Fivetran for your next warehouse migration.

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 more about how different teams can get in on improving data quality across the company.

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.

Learn about common data quality mishaps when implementing new tools for your data stack.

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

Metaplane's data observability platform adds smart monitoring suggestions and covers everything from Snowflake spend to dbt jobs.

We've overhauled the monitoring platform from the UI to under the hood.

Metaplane integrates Snowflake Data Metric Functions for robust, secure, and economical quality monitoring across your ecosystem.

Metaplane announces Snowflake Premier Technology Partner status - learn what this means for you

Learn more about data relevance and how it can improve your data quality.

Learn more about how data security plays a role in your data quality practices.

Learn more about how data reliability plays a role in your data quality practices.

Learn what data usability is and what role it has to play in improving data quality across your data stack.

Learn more about how valid data can play a part in your data quality strategy.

Data completeness 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 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.

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.

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.

Poor data quality creates extra work and frustrates stakeholders. At worst, it costs time, revenue, and damages customer sentiment.

How to choose the right data architecture: Weighing the pros and cons of Data Mesh and Data Fabric.

Your business is evolving, and so is business tech. Data modernization makes sure the tools you use to collect and analyze data keep up.

Learn more about how data quality tests, data monitoring, and data observability differ, while still improving data quality in their own ways.

Data observability is crucial for modern data teams. This blog defines it, distinguishes it from similar concepts, and highlights its importance.

Address data quality issues with guidelines, concepts, and practices to preserve trust and turn data into your greatest asset.

Explore data products' role in decision-making, their business impact, and the evolving implications of this concept in data strategy.

Understanding Microsoft Fabric: From OneLake's unique data storage to flexible compute setups.

Learn more about an up and coming space, machine learning monitoring, and how the use cases and functions differ from data observability.

Data catalogs improve quality and streamline teamwork. Learn key considerations if you’re evaluating options for your organization.

Learn how you can use data lineage, provided by data observability tools, to improve data quality across your modern data stack.

A detailed guide comparing Data Mesh and Data Lake architectures, and factors to consider when choosing.

A framework for data practitioners to evaluate data observability and quality monitoring tools.

Overview of the similarities and differences between the established field of Software Observability and the emerging category of Data Observability.

Business intelligence is evolving, and it's happening right now. Discover the 5 transformative shifts set to redefine the future of BI.

Discover how to effectively backfill data in 2023, manage complex challenges, and uphold high data accuracy standards.

Read this post to understand if you should formally assign or hire a member of your team to focus on data reliability.

Using stale data for decision-making can have dire consequences. In this blog post, we explore the risks and emphasize the significance of accurate data.

Data contracts bridge business and data workflows. Learn their key elements, benefits, and implementation strategies in our blog.

Discover the key trends shaping data analytics and data science: automation, the rise of machine learning and LLMs, and the democratization of data.