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Cuebook monitors your business metrics

Know when, where and why a metric isn't right. Ensure fast action.

Personalized and Autonomous Anomaly Detection at Scale

Cuebook uses machine learning to identify significant dimension combinations relevant for you, from amongst millions of combinations. For each combination, Cuebook learns the metric's normal behavior with weekly and daily seasonality, including holiday effects. Cuebook then monitors and alerts you when it finds an anomaly.

Autonomous Root Cause Analysis

Cuebook uses time-lagged lineage across your business metrics to automatically identify root causes for anomalies. You can instantly analyze non anomalous data as well.

Search-driven Insights and Anomalies

Search for any metric, dimension, value or a combination of these. Get instant insights and anomalies.

Collaboration

Collaborate with your team to take action.

Metric Lineage

Lineage across your business metrics, with time-lag.

Curation

See only relevant and significant anomalies. Additionally, curate anomalies. Say bye to false alerts.

Recent Posts

How to reduce Customer Churn via Anomaly detection?

A few years ago, I helped an Indian payments company build its data platform. The company provided card swipe machines to its customers. Its customers included large retail chains to mom-n-pop stores. The company had a huge feet-on-street team to … Read More

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Is Search-driven Analytics really about Search?

Say you want to search “augmented analytics”. You go to Google, enter “augmented analytics” and Search. You get 10 results from different websites on the home screen. Now imagine the following. You go to search engine XXX . You must … Read More

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What is Time-lagged Lineage of Metrics?

Say you work for a financial services company in the lending business. You receive loan applications that you process in exactly 2 days. For every 20 applications, you approve one. This means your approval ratio is 5%. Say below is … Read More

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