"Trendalyze is the first motif discovery platform to visualize, search, and monitor for micro-trends in time series data."
Trendalyze is the first motif discovery platform to visualize, search, and monitor for anomalies and/or recurring patterns in time-series data. It is built specifically to scale for big data and IoT sensor data in order to monetize data patterns.
Our innovative Google-like search approach, based on pattern shapes and deep learning, is both powerful and easy to use. Business professionals can investigate data patterns that reveal the root causes of events and set up real-time monitoring and alerting dashboards to improve outcomes in their industries without having to rely on IT or data scientists.
Pinpoint valuable micro trends (motifs or anomalies) interactively or with machine learning.
Search to discover similar micro trends in millions of time series to identify all actionable cases.
Set up monitoring dashboards and alerts for micro trends occurrences to enable real-time decision making.
The way that Trendalyze works is that you inspect time series data looking for microtrends
(motifs) that are of interest. Take predictive maintenance as an example. What you are trying to achieve is to predict when a particular asset is likely to fail and repair it before it does so. To do this you require a large body of historical time series data. The standard approach is to have a data scientist build machine learning or other algorithmic models that will make the relevant prediction. The concept behind Trendalyze, however, is that there will be specific micro-trends in the time series data that can be used to make these predictions and once a relevant motif has been found you can use this as your predictor. And, specifically, while it may be relatively easy to spot a pattern – when displayed visually – it is not easy to spot a recurrence of that pattern, let alone any slight variation on that pattern. This is what Trendalyze aims to automate for you. The software applies search principles to look for instances of an identified motif within the dataset being examined. Once discovered you can set threshold parameters around your motif (in other words, supporting variations to the motif), which can be used to predict assets that need maintenance.
We developed the first self service platform for the business professional to explore and gain insights from time series data, and monetize them through setting up monitoring dashboards and real time alerts. Micro trends discovery used to be done by experienced data scientists who created complex models. Not any more!
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