Monte Carlo, the data observability company, announced a new integration with the automated data movement platform Fivetran, giving users the ability to accelerate data incident detection and resolution by adding monitoring to data pipelines at the point of creation. With today's announcement, Monte Carlo becomes the first data company to bring data observability to the entire orchestration layer, after integrations with Airflow, dbt Core and dbt Cloud were announced in 2022.

The integration with Fivetran is the latest step in Monte Carlo's mission to bring end-to-end data observability to customers' data stack. Monte Carlo, which maintains rich integrations with data warehouses and lakes like Snowflake, Databricks, Google BigQuery, and Amazon Redshift, business intelligence tools like Looker, Tableau, and Mode, and ETL tools like Airflow and dbt, extends data quality coverage at ingestion with our native Fivetran integration. Now, data teams that rely on Fivetran to seamlessly ingest data into their warehouses and lakes can unlock the power of automated, end-to-end data observability to prevent bad data from affecting downstream consumers.

"Customers are at the core of everything we do at Monte Carlo, including driving what decisions we make with the evolution of our product," said Lior Gavish, co-founder and CTO of Monte Carlo. "We've seen incredible adoption of our dbt integration, which has demonstrated to us that customers require more and more visibility into the orchestration layer. And with Fivetran being one of our customers' favorite ELT tools, this new integration with Fivetran will be transformative and give them the ability to detect and troubleshoot issues faster so they can reduce data downtime and tackle initiatives that drive the needle for their business."

As part of this news, Monte Carlo is excited to announce an official partnership with Fivetran to help joint customers improve data reliability at scale across the modern data stack.

"Our customers understand how easy it is to build pipelines, automate the ingestion process, and scale easier with Fivetran," said Logan Welley, vice president of Alliances at Fivetran. "Joint customers of Monte Carlo and Fivetran now have the added benefit of having data observability built into those pipelines the moment they are built - allowing data teams to have full visibility of any upstream problems before they impact downstream users and products."

Reduce time and resources spent on data quality with end-to-end coverage

As companies ingest larger volumes of data and pipelines become increasingly complex, the opportunity for data downtime - periods of time when data is inaccurate or erroneous - only grows. Data engineers spend up to two days per week firefighting broken data pipelines, an expensive problem that costs data teams millions of dollars per year in wasted revenue. Launched in 2019, Monte Carlo's data observability platform helps data teams mitigate the risk and impact of data quality issues across the modern data stack by reducing the amount of time and resources it takes to detect and resolve them.

Our latest integration and partnership with Fivetran signals our commitment to making data more trustworthy and reliable by giving data engineers even more granular visibility into the health of their pipelines.

With this integration, mutual customers can now:

• Achieve end-to-end data observability across ELT: Get end-to-end data observability for Fivetran data pipelines with a quick, no-code implementation process. Access out-of-the-box visibility into data freshness, volume, distribution, schema, and lineage just by plugging Monte Carlo into Fivetran.
• Know when data breaks, as soon as it happens: Monte Carlo continuously monitors your data assets and proactively alerts stakeholders to data issues. Monte Carlo's machine learning-first approach gives data teams broad coverage for common data issues with minimal configuration, and business-context-specific checks layered on top ensure coverage at each stage of ELT - and beyond.
• Find the root cause of data quality issues, fast: Monte Carlo gives teams a single pane of glass to investigate data issues, drastically reducing time to resolution. By bringing all information and context for pipelines into one place, including Fivetran logs, teams spend less time firefighting data issues and more time building.

With the Monte Carlo - Fivetran integration, monitoring coverage is automatically integrated the moment the pipeline is built. When an issue occurs, notifications are surfaced within the Monte Carlo UI and sent as alerts in Slack, Microsoft Teams, PagerDuty and anywhere else you manage incident workflows.

What our mutual customers have to say

Mutual customers like Backcountry, Checkout.com, and Masterclass are already leveraging both tools to improve data observability across their pipelines:

"Earlier when we had issues related to accuracy and efficacy of our data pipelines, Monte Carlo helped us get to a place where we could have a good idea of when things might be going south upstream," said Prasad Govekar, director of data engineering, data science & analytics at Backcountry.com. "When you're leading a tight-knit data team and trying to improve data trust, understanding when data breaks is only the first step. Integrating Monte Carlo at the point of ingestion allows us to understand impact, and therefore provide greater visibility to key stakeholders. Having end-to-end lineage with Fivetran is a game changer that is helping us reduce time to detection and resolution for data incidents, and in the process, increasing trust with our stakeholders."