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OpenTSx: Streaming Time-Series-Analysis (TSA) for the cloud.

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Creation of time series datasets

In order to analyse time series data it is essential to prepare the raw data for efficient access. You have to 'bring data in shape', so that algorithms can safely process the data while keeping the real meaning.

Generate time series using time series models

Currently we provide example time series generators of the following series types:

1. White noise
2. Random values (of multiple distributions)
3. Random values (of multiple distributions) including long term correlations

Load time series from IoT metrics stores.

Using a standardised telemetry data schema we extract metrics from various time series data stores. We align data points and episodes within the scene context. This enables multivariate time series analysis and contextual awareness across multiple domains.

Load Server metrics.

Reading time series data from metrics stores allow advanced systems analytics. This is another typical field of application in the technical context.

Load Financial data from Internet.

Since this toolbox is not bound to tech-data only, we show examples from financial services.

Load Medical time series data from Internet

Another typical field of application is medical data analysis.