Published inTowards Data ScienceRunning Timeseries Anomaly Detection at Scale on SQL DataMulti-dimensional data, SQL, Pandas, and ProphetAug 27, 2021Aug 27, 2021
The 1% RuleWhy 99% of business users find it hard to use a self-serve data platform. Because it’s actually DIY.Apr 29, 2021Apr 29, 2021
How to reduce Customer Churn via Anomaly detection?How you can use anomaly detection to identify customers likely to churn? And also provide required information to reduce churn.Apr 19, 2021Apr 19, 2021
What is Time-lagged Lineage of Metrics?How time-lag in your funnel impacts derived metrics.Apr 16, 2021Apr 16, 2021
Anomaly Detection at ScaleWhy anomaly detection at scale is hard, expensive and noisy.Apr 14, 2021Apr 14, 2021
Is Search-driven Analytics really about Search?or is it natural language query being sold as Search?Apr 13, 2021Apr 13, 2021
Root Cause Analysis — a StoryLet’s say I recently joined a fictitious online fashion store as an analyst. One morning I receive a message from Bill, our VP of…Apr 9, 2021Apr 9, 2021
What is an Anomaly?Anomaly is when a metric deviates from normal. But how do you define what is normal?Apr 3, 2021Apr 3, 2021
Anomaly Detection: Business metrics vs. Technical metricsWhy anomaly detection for a business metric differs from that for a technical metric.Mar 28, 2021Mar 28, 2021
The Wealth of Nations — an Indian Entrepreneur’s takeAs an entrepreneur in India, I frequently came across comparisons of Indian and Chinese economies — Indian economy is just 10–15 years…Jul 27, 2018Jul 27, 2018
