Scatter plots
Trending data is good for visualizing data over time, but it can be difficult to compare different tags by looking at a trend. This is where scatter plots become useful.Scatter plots give you a better understanding of correlations between properties when looking at a small number of dimensions at a time. If you have a scatter plot of two tags, and would like to know how this has evolved over time, you can add time as coloring, as you can see above. Coloring can be continuous or categorical. You also have the option to view data in 3D plots
Parallel Coordinate Plots
Quite often data exploration can become challenging. There are multiple variables involved, which can be difficult to visualize. This is where parallel coordinate plots can help. Parallel coordinate plots is an efficient way to visualize and analyze high-dimensional datasets. Parallel coordinate plots are available both for raw time series data and segmented data.
Overlaid segments
This type of plot is specifically tailored to segmented data and enables efficient comparison of time series curves over distinct segments or batches.
A common use case is to observe how a value evolves through production batches over time. This could be any variable of interest, such as temperature, vibration, yield or capacity. The analysis is not limited to batch data; it can also be used e.g. to compare daily power consumption patterns.
Collaboration
Share Data Explorer results with colleagues inside (or outside) your company. Take a snapshot of an analysis, and securely share it with anyone, even if they don’t have an Intelecy account. The exported reports are self-contained (all data is embedded in the report), fully interactive (users can zoom, filter, print) and can even be saved for offline access.