Advertising TechnologySourced

Case Study: Choozle reduced data downtime by 88% with Monte Carlo

Choozle Case StudySourced & dated by Case Study Desk

Key facts · TL;DR

Company

Choozle

Industry

Advertising Technology

Challenge

An AdTech platform needed alerting coverage across thousands of tables without compromise.

Headline result

Choozle reduces data downtime by ~88% and extends alerting across all 3,500 tables

Key results

88%

Reduction in data downtime

approximately

3,500

Tables with alerting coverage

1 hour

Incident resolution time

down from a full day

The challenge

Choozle, a self-service digital advertising platform, managed about 3,500 tables. Data downtime and slow incident detection risked the reliability of its advertising data.

The solution

Choozle deployed Monte Carlo to provide alerting across all 3,500 tables and accelerate detection and resolution of data incidents.

“With Monte Carlo we are at a level where we don't have to compromise. We can have alerting on all of our 3,500 tables.”
AW
Adam Woods
Chief Technology Officer, Choozle

The results, in context

Choozle reduced data downtime by approximately 88% and extended alerting across all 3,500 of its tables. The CTO reported incidents are now resolved in about an hour rather than a full day, with time-to-detection cut from days to minutes.

Products used

Monte Carlo Monte Carlo Data + AI Observability Platform