Step 4: Validate Data

Prerequisite: You should have multiple tags flowing from Step 3. If not, complete that first!

The Problem

Right now, ALL your data goes into _raw - no validation:

• DB1.DW20 could suddenly send "hello" instead of a number

• Critical vibration data might arrive with wrong units

• Typos in tag names create duplicate data streams

How do you ensure data quality? Data Models!

Part 1: Create Your First Data Model

Let's create a model for a CNC machine's vibration data.

Add a Data Model

1. Go to Data Models → Add Data Model

2. Instance: Select your instance

3. Name: cnc

4. Description: "CNC machine vibration monitoring"

Define the Structure

In the Data Model Structure section, add this YAML:

vibration:
  x-axis:
    _payloadshape: timeseries-number
  y-axis:
    _payloadshape: timeseries-number

What this means:

• Your CNC model has a vibration folder

• Inside are two measurements: x-axis and y-axis

• Both must be numbers (enforced automatically!)

Data Model Creation

Click Save & Deploy.

Data Model List

💡 Behind the scenes: The system automatically creates a data contract called _cnc_v1. This contract will enforce your model's structure. Learn more about data contracts →

Part 2: Use Your Model in a Bridge

Find Your Contract Name

1. Go to Contracts tab

2. Find _cnc_v1 - this was auto-generated from your model

3. Note the structure it expects

Contract View

Update Your Bridge

Go back to your S7 bridge from Step 3. In the Always section, change:

// OLD: Everything goes to _raw
msg.meta.data_contract = "_raw";

To:

// NEW: Everything goes to our validated model
msg.meta.data_contract = "_cnc_v1";

Incorrect Processing Setup

Click Save & Deploy.

Part 3: Experience Validation (It Will Fail!)

Deployment Failed

Your deployment fails! Look at the error:

schema validation failed for message with topic 'umh.v1.enterprise.sksk._cnc_v1.DB1.DW20':
Valid virtual_paths are: [vibration.x-axis, vibration.y-axis].
Your virtual_path is: DB1.DW20
Fix: Update the bridge to set meta.virtual_path to 'vibration' and meta.tag_name to 'x-axis' or 'y-axis'

Data models ENFORCE structure. Your S7 address DB1.DW20 doesn't match the expected paths vibration.x-axis or vibration.y-axis.

Two new concepts here:

1. Deployments can fail not only if the connection is bad (learned in Step 2)

2. But also if the bridge throws validation errors

Part 4: Fix with Smart Routing

Instead of forcing ALL data into the model, let's be selective. Change your Always section back:

// Most data stays unvalidated
msg.meta.data_contract = "_raw";
msg.meta.tag_name = msg.meta.s7_address;
return msg;

Now update your condition for DB1.DW20:

// Special handling for DB1.DW20: Route to validated model
msg.payload = parseFloat(msg.payload) * 1.0;
msg.meta.data_contract = "_cnc_v1";  // Use validated model
msg.meta.virtual_path = "vibration";  // Required: matches model structure
msg.meta.tag_name = "x-axis";         // Required: matches model field
msg.meta.unit = "raw";
return msg;

Correct Processing Setup

What this does:

• DB1.DW20 → Validated as vibration.x-axis in CNC model

• All other tags → Continue to _raw (no validation)

Click Save & Deploy. Now it succeeds!

Part 5: Success! View Your Validated Data

Topic Browser with Validated Data

In Topic Browser, you now see:

enterprise.sksk._cnc_v1.vibration.x-axis    [12345]  ✓ Validated
enterprise.sksk._raw.DB1.S30.10             ["text"]  (Unvalidated)
enterprise.sksk._raw.DB3.I270               [789]     (Unvalidated)

How validation works:

• The CNC model guarantees x-axis is always a number

• If someone sends text, it's rejected at the bridge

• Other data flows normally through _raw

Concepts Learned

Building on previous guides, you now understand:

• Data Models - Reusable templates defining data structure

• Payload Shapes - Type validation (timeseries-number, etc.)

• Schema Validation - Automatic enforcement at the bridge

• Auto-generated Contracts - Models create contracts like _cnc_v1

• Validation Errors - Deployments fail if data doesn't match

• Selective Validation - Route specific data to validated models

What's Next?

You now have a complete data pipeline with:

• ✅ Automatic tag discovery (Step 3)

• ✅ Smart organization (Step 3)

• ✅ Data validation (Step 4)

Ready for production? Check out:

• Production Guide - Sizing, security, monitoring

• Data Modeling Deep Dive - Advanced models

• Stream Processors - One way to transform device data to business KPIs

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Congratulations! You've mastered the fundamentals of UMH Core. Your data is now organized, validated, and production-ready. 🎉