Source: thenewstack.io
Tools for Time-Series Data Science Problems with InfluxDB
https://www.linkedin.com/in/anais-dotis-029623113/ You might need to perform anomaly detection or forecasting if you’re working with time-series data. Time-series databases stand out from more common relational databases because instead of using rows and columns to quickly find relationships between data points, they are designed to handle the unique workloads of time-series data.
We’ll also discuss some of the enhancements to InfluxDB v2 Python Client Library that make querying data from InfluxDB and applying data science tools to your time-series data easier.
https://adtk.readthedocs.io/en/stable/ (anomaly detection tool kit) is an open source Python package for rule-based anomaly detection in time-series data.
While you can use InfluxDB for some basic forecasting or anomaly detection, you’ll likely want to use a client library to query your data and tackle your data science problems with other purpose-built tools.
We’ll also discuss some of the enhancements to InfluxDB v2 Python Client Library that make querying data from InfluxDB and applying data science tools to your time-series data easier.
https://adtk.readthedocs.io/en/stable/ (anomaly detection tool kit) is an open source Python package for rule-based anomaly detection in time-series data.
While you can use InfluxDB for some basic forecasting or anomaly detection, you’ll likely want to use a client library to query your data and tackle your data science problems with other purpose-built tools.
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