How to Use Time Series Data to Forecast at Scale
Session date: Jul 24, 2019 10:00am (Pacific Time)
The growing popularity of IoT, sensor networks, and other telemetry applications lead to the collection of vast amount of time series data which enable forecasting for a multitude of use cases from application performance optimization to workload anomaly detection. The challenge is to automate a historically manual process handcrafted for the analysis of a single data series of just tens of data points to large-scale processing of thousands of time series and millions of data points.
In this talk, we will show how to leverage InfluxDB to implement some solutions to tackle the issues of time series forecasting at scale, including continuous accuracy evaluation and algorithm hyperparameters optimization. As a real-world use case, we will be discussing the storage forecasting implementation in Veritas Predictive Insights which is capable of training, evaluating and forecasting over 70,000 time series daily.
SPEAKERS: Thom Crowe, Community Manager at InfluxData Marcello Tomasini, Sr. Data Scientist at Veritas
