Henry Li

Engineering

Making sense of machine learning and artificial intelligence models by monitoring the training data

When you're training ML /AI models, the input data selection process matters. Build solid ML/AI model performance with data observability.

Henry Li

Thought leadership

Data anomaly detection requires hindsight and foresight

While anomaly detection comes in many forms, there are two major approaches: ex ante and post hoc. Ex ante means before the event, which is a prediction of the future. Post hoc means after this, which is reasoning after all events have already occurred.

Henry Li

Company

Automating data observability at scale

Scale observability so that data users can focus on solving business problems instead of dealing with data issues.

Henry Li

Product

Anomaly Detection Part 2: The Bigeye Approach

This is the second blog in a series on anomaly detection from Henry Li, Senior Data Scientist at Bigeye.

Henry Li

Product

Anomaly detection part 1: The key to effective data observability

Anomaly detection is critical to effective data observability. In this blog, Henry Li, senior data scientist at Bigeye, dives into three of the most important aspects of anomaly detection.

Henry Li

Engineering

Lessons Learned from Uber: Designing an Intelligent Data Quality Monitor

In this blog, I will discuss the considerations that should be made before undertaking a data quality initiative.

Henry Li