Trends

Data Reduction

The Data Reduction section controls how large datasets are simplified for display in the Trend Viewer. This ensures optimal performance and readability, especially when dealing with high-frequency or long-term data.

Active

Enables or disables all data reduction features.

• If enabled, the system applies one of the selected reduction methods below.
• If disabled, all original data points are shown, which may impact performance.

Max Points

Defines the maximum number of points displayed after reduction.

• Lower values improve speed and responsiveness, but reduce detail.
• Higher values preserve more precision, but may cause slowdowns on weaker systems.

Reduction Type

Method	Description
Quick Reduce	Fast sampling method. Optimized for speed. May skip some important values.
Reduce	Balanced approach (similar to LTTB). Preserves trends while removing redundancy. Handles null and special values properly.
Local Extremes	Keeps local min and max for each time segment. Ideal for detecting spikes or dips.
Average	Calculates the mean value per interval (simple moving average). Smooths out fluctuations.
Median	Splits data into intervals and returns the median of each. More robust against outliers than average.

Note: These settings affect only how data is rendered — not how it's stored. Choose the right method depending on whether you prioritize accuracy, outlier visibility, or performance.