Data Quality, Data Platforms

Monte Carlo Now Surfaces Hex Projects and AI Apps Impacted By Poor Data Quality

Michael Segner

Michael writes about data engineering, data quality, and data teams.

meitao

Mei Tao

Product at Monte Carlo

Hex is one of the fastest growing collaborative data exploration solutions for a reason, it allows both technical and non-technical users to explore data, derive insights, and build powerful data applications for further visualization and exploration.

A sample Project from the demo on the Hex homepage.

Hex is a powerful way to bring analytics, data science, and business users together to answer tough business questions…but only if the data populating the project can be trusted. Any data consumer facing issues can erode that trust and ultimately adoption.

Hex projects also often serve as the foundation for machine learning and AI applications that automate processes and drive revenue…but only if the data guiding and fueling the model is high quality. Bad data can turn an AI application from an asset into a liability quickly.

Now Monte Carlo automatically, without requiring any additional setup, visualizes data lineage dependencies between data warehouse/lake/lakehouse tables and Hex projects. This allows data teams to more quickly understand, respond, and fix high priority incidents before they can negatively impact the business.

“Organizations can’t drive value with innovative data apps and AI models without highly reliable, high quality data,” said Barr Moses, CEO and co-founder, Monte Carlo. “We are heavily investing into capabilities that bring additional visibility, and reduced data downtime, to these critical data and AI assets.” 

Tracing Lineage From Ingestion To Consumption

The new Hex integration further enriches Monte Carlo’s industry leading data lineage capabilities, which provide a single pane of glass for data teams to understand the dependencies between incidents, ingestion connectors, streaming syncs, orchestration DAGs, transformation models, tables, BI reports, and now Hex projects.

The Hex Project “Churn Analysis” leverages data from the Snowflake table “client_hub.”

Additionally, every alert within the Monte Carlo platform will contain an automatic impact assessment highlighting the specific Hex projects, if any, that will be affected by the anomaly.

The data in this table flows to more than 50 reports downstream including these Hex projects.

Hex projects will also be discoverable within the Monte Carlo asset listing alongside tables, reports, fields, and jobs.

Hex projects are populated and easily discoverable within the Monte Carlo Assets tab.

More than 38 customers, including Calendly, currently leverage Monte Carlo’s Hex integration.

“Hex is a critical part of our data stack at Calendly – it quickly became a top tool for our analytics community to improve both customer and ad spend insights,” said Noah Abramson, Senior Engineering Manager Data and Analytics, Calendly. “This integration has given our team the visibility we need to immediately understand when the value driven by those data products may be at risk. It’s also given our stakeholders confidence that they can trust the insights and decisions made by these data products.”

To learn more about Monte Carlo’s Hex integration, see our documentation or request a demo.

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