Integrating Monte Carlo’s Data Observability Platform With Sigma
Business users are more likely to regularly access and use data they can trust. Each data quality incident or stale dashboard depreciates that precious asset.
Sigma workbooks allow users to glean insights and intuitively explore your organization's data, but as we all know what they see is the result of a series of highly complex, interdependent operations across a data pipeline. Data freshness or other quality issues can arise from complications at any stage of this pipeline–from ingestion and orchestration to transformation and visualization.
Sigma’s integration with Monte Carlo’s data observability platform helps mutual customers to ensure their pipelines–and the data flowing through them–that feed their Workbooks is reliable and trustworthy.
Read more about all of Sigma’s connections here.
Data observability solutions like Monte Carlo leverage machine learning monitors and pipeline metadata to automatically detect data quality incidents at scale across the customer’s entire environment without requiring any manual rules or threshold setting.
The data team member responding to the incident can quickly assign an owner, severity level, and incident status, such as, “investigating,” within Monte Carlo, and have the updates visible for workbook page users in Slack, Microsoft Teams, or the collaboration tool of choice for the organization.
And when a data incident does occur, data teams can quickly trace the impact downstream to affected Sigma workbooks with automated data lineage.
Read about data lineage in Sigma here.
This integration requires no setup or configuration. Sigma workbook pages will automatically surface as lineage nodes and catalog entries once users have connected their Monte Carlo environment to Snowflake, BigQuery, Redshift, or Athena (see more details here).
Here is what our mutual customers have to say about the integration:
“Sigma empowers our data and business teams to collaborate and turn analytics into business value. Getting insight into how the impact of an incident could reverberate downstream to our workbooks is essential to maintaining and expanding that collaboration,” said Lior Solomon, VP of Data at Drata. “We’re excited to leverage Monte Carlo’s Sigma integration to bring data trust to the downstream dashboards and reports our company relies on to power growth and decision making.”
“Sigma is the nexus where our data and business teams meet to collaborate and turn analytics into business value. Getting insight into how the impact of an incident could reverberate downstream to our workbooks is essential to maintaining and expanding that collaboration,” said Mark Stange-Tregear, VP of Data, Babylist. “Monte Carlo’s integration is already proving valuable in providing us end-to-end visibility across our data assets.”
To get the full picture, check out the 90-second video here or visit the Monte Carlo documentation page.
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