Why Data quality flags in SCADA systems? - Purpose & Use Cases

The Big Idea

What if your system could instantly tell you which data to trust and which to ignore?

The Scenario

Imagine you are monitoring a factory's machines manually, checking each sensor reading by hand to decide if the data is good or if something is wrong.

The Problem

This manual checking is slow and easy to miss errors. You might trust bad data or waste time fixing things that are actually fine.

The Solution

Data quality flags automatically mark sensor data as good, questionable, or bad. This helps you quickly trust or ignore data without guessing.

Before vs After

✗ Before

Check each sensor reading manually and write notes about quality.

✓ After

Use data quality flags to label readings automatically as GOOD, BAD, or UNCERTAIN.

What It Enables

It enables fast, reliable decisions by clearly showing which data can be trusted and which needs attention.

Real Life Example

In a power plant, data quality flags help operators know instantly if a temperature sensor is faulty, preventing wrong actions and costly downtime.

Key Takeaways

Manual data checks are slow and error-prone.

Data quality flags automate trust decisions on sensor data.

This leads to faster, safer, and more confident operations.