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Cleaning and Interpreting Time-series Metrics with InfluxDB
Metric data can benefit from being standardized and condensed before being stored in your database. It can also be useful to be able to search and filter the data outside of your database. The flux data processing language is built for handling these tasks in the Flux VS code tool.
Raw time series metrics data can benefit from clean-up and normalization before exposing it for broader use and storage. When dealing with large amounts of time series metrics, it can be helpful to be able to standardize the ways in which others can search through that data for specific time frames using easy to understand tags. This talk focuses on using Flux, InfluxDB’s data processing language, for addressing these challenges. Examples of how to leverage Flux to accomplish data cleansing and analytics through the browser and via Visual Studio will be demonstrated.
More about Zoe Steinkamp
Zoe Steinkamp is a Developer Advocate for InfluxData. She has worked for InfluxData as a front end software engineer for over two years. Before InfluxData, she worked as a front end engineer for over 5 years in the original AngularJS. She originally went to a bootcamp for training in Python. Her favorite activities outside of work include traveling and gardening.