Guide
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Review PI exception and compression settings to improve data precision, reduce hidden signal loss, and align historian settings with how tags are actually used.
THE CHALLENGE
PI compression reduces stored data, but settings that are too aggressive can remove important process detail.
The problem is not always obvious. Trends can still look reasonable while calculations, investigations, analytics, or quality reviews lose the precision they need.
Changing compression without understanding tag usage can also create unnecessary storage and system load.
1
Assess
Review current exception and compression settings across the selected PI environment.
2
Analyze
Compare stored signal behavior, configuration, and tag usage.
3
Prioritize
Identify tags where settings create the highest precision or performance risk.
4
Recommend
Provide specific changes for engineering review and implementation.
THE SOLUTION
Optimize compression based on signal behavior and tag usage
Tycho reviews PI exception and compression settings together with historical signal behavior and downstream usage. Teams can identify tags that may be over-compressed, under-compressed, or configured inconsistently with their operational purpose.
The result is a prioritized set of recommendations that balances precision, performance, and storage.
Engineering effort stays focused on the settings with the greatest operational impact.
PRECISION RISK
Find settings that remove important process detail
Identify tags where compression may hide meaningful changes in process behavior.
What this covers:
Excessive compression
Exception settings
Loss of signal detail
Precision-sensitive measurements
TAG USAGE
Understand how the data is used before changing settings
Use OT lineage to see which calculations, displays, reports, and applications depend on each tag.
What this covers:
AF dependencies
Analysis usage
PI Vision usage
Downstream consumers
CONFIGURATION CONSISTENCY
Find settings that do not match engineering intent
Compare similar tags, assets, and measurement types to identify inconsistent historian configurations.
What this covers:
Inconsistent compression settings
Engineering standard gaps
Similar tags with different configurations
Configuration outliers
STORAGE & PERFORMANCE
Reduce unnecessary data without sacrificing useful detail
Identify tags that store more data than needed and distinguish them from signals where additional detail has operational value.
What this covers:
High event counts
Low-value stored data
Storage optimization opportunities
Historian efficiency
COMMON USE CASES
When Compression Optimization helps
Critical process monitoring
Preserve detail needed to understand important equipment and process behavior.
Quality & compliance reporting
Reduce the risk that historian settings hide meaningful process variation.
SPC and analytics
Improve the precision of data used for statistical analysis and modeling.
Historian performance
Reduce unnecessary event volume without blindly increasing compression.
Standards enforcement
Align compression settings across similar instruments and assets.
Migration & modernization
Review historian settings before carrying poor configurations into a new environment.
Frequently Asked Questions
Get answers to common questions here
TAG COMPRESSION OPTIMIZATION