Time-series anomaly detection is used to identify unusual patterns that do not conform to expected behavior otherwise know as outliers. There are a number of business applications for this type of machine learning. For example, IoT use cases where an unusual traffic pattern that might indicate an issue with a traffic light and business applications like detecting strange network behavior that could indicate a hack attempt.
We provide a number of anomaly forecasting algorithms within the workspace so you can determine the best one for your specific use case. To use, simply select Anomaly Detection as your machine learning option and create a new workspace. Follow the configuration steps and test out different algorithms for accuracy. The precision of the model increases over time as more data is made available.
The anomaly detection visualization itself consists of a configurable blue band range of expected values (acceptable threshold limit) along with the actual metric data points. Any values outside of the blue band range are considered anomalies and will appear in red.
Sparkly New Data Visualizations
You may think data grids are boring but then you haven't tried our new data grid visualization. You can do a ton with this new grid type, including formatting, conditional highlighting, sorting, grouping, and search along with the ability to download formatted grid information in Excel format.
The other pretty cool thing you can do is add charts to cells. The embedded chart options are sparkline, area, bar, spline, spline area, and pie. Not so boring anymore, right?
Image Overlay Heatmap
You can now upload an image and overlay x, y coordinate values. Example use cases are tracking how a stadium is filling up as people are scanned at the entry gates or showing the location of IoT sensors deployed on each floor of a building.
It's Your Dashboard - Customize It!
We enhanced the level of customization of the look and feel of your dashboards by adding several new configurable options.
Getting Clicky With It
Tightly integrating Knowi visualizations within your applications is an important step to give users a seamless experience. To further that integration, we've added an OnClick Event Handler which is available for various visualizations. You can use it to customize what action to take when a data point is clicked on the visualization.
Please sign in to leave a comment.