Use cases
outcome
75%
faster data issue resolution
100s of manual checks
eliminated
tech stack
Impira uses Bigeye as the safety net for its dynamic go-to-market strategy — ensuring that the team can move fast with reliable data.
About Impira: Unlocking and unifying data
Impira is a venture-backed startup whose platform automatically extracts data from unstructured documents through flexible machine learning. The company's no-code, self-service platform makes it easy for companies of all sizes to create their own automations to unlock and unify their data. With customers that span from Airbnb and Stitch Fix to Colgate and Tom’s of Maine, Impira relies on accurate data to drive their go-to-market strategy.
Challenge: Move fast and break things
Impira analyzes a huge amount of data to fuel its self-service go-to-market strategy. By examining “aha” moments in the customer journey, the product team can see how customers flow through the implementation process, quickly iterate, and improve the customer experience.
Impira is moving fast and continually making important decisions on product usage data. Uncaught problems in that usage data could seriously impact their go-to-market decisions, causing them to focus resources on the wrong part of the customer journey. Because such a critical part of the business depends on reliable data, but the longer an issue goes undetected, the more problems it creates down the road.
Before implementing Bigeye, Impira’s go-to-market team identified data issues manually, creating firefighting moments for the data engineering team, and slowing down their decision-making process. The team needed more freedom to make key decisions with the assurance that the data was right.
Solution: Creating a safety net with Bigeye
The Impira team quickly went to work applying Bigeye’s built-in metrics for measuring freshness, duplicates, and cardinalities. Autothresholds, which dynamically set and adjust alert thresholds for them, giving them 24/7 automated monitoring and alerting in place of their manual spot checks.
Now, Bigeye continuously monitors Impira’s customer usage data, alerting the data team to any issues before the data is used by the product management team. The early detection they get from Autothresholds-based alerts also ensures that one issue doesn't balloon into more issues — saving valuable engineering time and ensuring that the product management team can move fast with reliable data.
Bigeye is able to detect a wide range of issues from cardinality explosions created by a bad SQL join, to very subtle bugs that violate uniqueness expectations. The Impira team told us that issues that now take one day to resolve, previously took four days of manual investigation, and even more time cleaning up everything else that was affected while the issue went undetected.
Result: Empowered to embrace risk
“We believe in embracing risk. When you are moving as fast as we are, you have to get over the idea that there is a world of zero outages. With Bigeye, those outages won’t slow us down. We know Bigeye will detect any issues before they affect the business,” said Ankur Goyal, CEO of Impira.
Impira is a small, fast moving team. With Bigeye automating their previously manual spot checking, they get hours back to invest in their go-to-market effort, and the confidence that the decisions they make with their customer journey data are backed by fresh, reliable data.
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