Creating a Monitor

Actian Data Observability : Monitoring Data : Monitors Management : Creating a Monitor

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Creating a Monitor

Starting Monitor Creation

Navigate to the Alerting Monitors page
Select the asset you want to monitor from the left sidebar
Click the "+ New Monitor" button in the top-right corner

Monitor Creation Panel

The monitor creation panel opens on the right side with two main sections:

Section 1: Monitor Policy: Choose your monitoring type

Section 2: Configuration: Set thresholds and conditions

Section 3: Notification: Set notification channels [optional]

Section 4: Ticketing: Set auto-ticketing requirements [optional]

Choosing Monitor Type

Select from three monitor types based on your monitoring needs:

Built-in Metric
User-Defined Metric
Record Validation Rule

Important: Monitor type cannot be changed after creation. Choose carefully based on your monitoring requirements.

Configuration Section

After selecting your monitor type, configure the monitor details:

Basic Information

Section	Details
Monitor Name (Required)	Must be unique per asset Use descriptive names that clearly indicate what's being monitored Example: `sales_data_freshness_check`, `email_validation_monitor`
Description (Optional)	Add context about: What the monitor checks Why it's important Expected behaviour Remediation steps
Monitor Tags (Optional)	Organize monitors using tags: Add multiple tags for categorization Use consistent tagging across monitors Examples: `critical`, `daily-check`, `revenue-impacting`
Impact (Optional)	Set the severity level for alerts generated by this monitor: High: Important issues requiring prompt resolution Medium: Notable issues that should be addressed Low: Minor issues for awareness

Configuring Built-in Metrics

When you select Built-in Metric, you'll see the predefined metric configuration section.

Data Quality Metric (Required)

Select from available predefined metrics:

record_count: Total number of records
null_percentage: Percentage of null values
freshness: Time since last data update
completeness: Data completeness score
uniqueness: Duplicate detection
schema_drifts: Schema change detection
And more...

Attributes (Optional)

For metrics that support attribute-level monitoring:

Select specific columns to monitor
Leave blank for table-level metrics
Multiple attributes can be selected
Examples:
Monitor uniqueness on customer_id field

Configuring User-Defined Metrics

When you select User-Defined Metric, you can define custom metrics using expressions or SQL.

Method 1: Expression-Based Metrics

Write simple aggregations with grouping. Example:

AGGREGATION(`attribute`) GROUP BY `dimension1`, `dimension2`

See full expression documentation for more examples.

Method 2: Custom SQL Queries

Write SQL queries for complex monitoring logic. Example:

SELECT AVG(order_value), customer_region, product_category
FROM `orders`
WHERE order_date >= CURRENT_DATE - 30
GROUP BY customer_region, product_category

See push down SQL documentation for more examples.

Configuring Record Validation Rules

When you select Record Validation Rule, you define checks for individual records.

Rule Definition

Write validation expressions for row-level checks:

Syntax:

validate CONDITION expect TELM_EXPECTATION

See record violation rules for more examples.

Threshold Configuration

All monitor types require threshold configuration to determine when alerts are triggered.

Threshold Types

Choose from three threshold approaches:

Automatic (ML-Based)

Let machine learning determine dynamic boundaries based on historical patterns.

Best for:

Metrics with seasonal patterns
Establishing initial baselines
Adapting to data evolution

Acceptable Drift %

Set percentage-based boundaries using moving averages.

Best for:

Relative comparisons to recent performance
Allowing controlled variance
Gradual data changes
Configuration:
Define acceptable drift percentage: Set minimum & maximum drift percentage values

Acceptable Range

Define constant, fixed boundaries.

Best for:

Hard business rules
Strict compliance requirements
Known acceptable limits
Configuration:
Set minimum & maximum value

Additional Configuration Options

Compare to Past # Scans

Specify how many historical datapoints to consider:

More scans = more stable baseline
Fewer scans = more responsive to recent changes
Default: Automatic (system-determined)

Replace Missing Values

Choose how to handle gaps in your metric time series:

Ignore: Skip missing datapoints
Use average: Fill with calculated average
Use zero: Treat missing as zero

Notification & Ticketing Configuration

Each monitor can be configured to send alerts and automatically create tickets when data quality issues are detected. These settings help ensure the right teams are notified and issues are tracked through resolution.

Configure where alerts should be sent when this monitor detects data quality issues.

Setting Up Alert Channels

Click + Add Channel in the Notifications section
Add as many predefined notification destination as needed
Use the Enabled toggle to activate or deactivate notifications for this monitor

Note: Notifications are marked as OPTIONAL. Monitors will continue to function and track data quality even without configured alert channels.

Learn more about managing alert channels

Ticketing

Enable automatic ticket creation to track and manage data quality issues through your existing workflow tools.

Auto-Ticketing Setup

When enabled, Data Observability automatically creates a ticket in your ticketing system whenever this monitor's policy conditions are met. This ensures data quality issues are formally tracked and assigned for resolution.

To enable auto-ticketing:

Check the Create ticket automatically checkbox
Select a ticket Template from the dropdown
- Templates define ticket fields, priority, assignment rules, and other properties
- Templates must be configured in advance in your ticketing integration settings
Save your monitor configuration

Note: Ticketing is marked as OPTIONAL. This feature requires a configured ticketing integration and defining templates before this feature is enabled. Learn more about managing ticketing integration with Jira.

Saving Your Monitor

Save and Cancel Actions

After configuring your monitor:

Review all settings
Click "Save" to create the monitor or click "Cancel" to discard changes

What Happens After Saving

Monitor is immediately created and enabled (by default)
Appears in the monitor list for the selected asset
Begins evaluating data according to configured schedule
Will generate alerts when thresholds are violated