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Data Observability
Proactively monitor and manage the health of your data. Receive actionable insights through alerts that drive business decisions.
Observers
You can create observers to keep a watch on your data assets and take timely measures in case of data anomalies. The observer monitors your selected data assets and provides alerts based on the selected observer rules.
Manage Observers
You can manage your observers on the Observers page.
Create an Observer
You can create multiple observers for a single data connection, but you cannot use the same assets across different observers. You must set up a successful data connection before creating an observer. To create a data connection, refer to DISuite/Observability/data-connections/Creating_Snowflake_Data_Connection.html.
Observer Rules
Observations profile your data on a regular cadence. It observes and monitors your data to identify anomalies. Based on your selected observations, you will receive alerts for identified anomalies. You can use observer rules to generate trends that can help you to identify business impacts and take prompt actions.
Data Drift Rule Configuration
You can track a set of statistics for Numeric and Textual data such as Cardinality (number of distinct values), min/max values, min/max length, number of empty/blank values, new values found, and so on. The unexpected changes in the historical trends of any of these statistics can impact overall decision-making. Data drift configuration generates alerts for unexpected changes in the selected statistics. The alerts will be generated if the value of the selected statistics increases or decreases than its expected value.

Welcome
The Precisely Data Integrity Suite is designed to deliver trusted data with accuracy, consistency, and context – built on the core capabilities of data integration, data quality, data governance, location intelligence, and data enrichment.
Data Integration
Replicate data from mainframe, IBM i, and relational databases to cloud analytics platforms.
Data Observability
Proactively monitor and manage the health of your data. Receive actionable insights through alerts that drive business decisions.
- Observe Data Assets
  Observing your data assets allows you to take actions based on the alerts received. Alerts are provided after successful scheduled runs. The trends generated provide alerts about data anomalies. You can observe data assets only once and cannot use them again for another observer. Before you create an observer, identify your data source and set up a data connection. Scheduling is mandatory for creating an observer.
- Profile Data Assets
  Learn about how to perform end-to-end Data Profiling. It provides a complete workflow of Data Profiling.
- Data Connections
  Your organization may have diverse data sources that you want to process. Use Data Connection to configure these data sources and connect them to the Data Integrity Suite.
- Data Profiles
  Data profiling scans your data records from all the data sources - irrespective of their volume and complexity. It identifies problems related to correctness, completeness, and validity in the data, and suggests actions to fix the issues. Thus, it improves the quality and utility of your data with very little manual effort.
- Observers
  You can create observers to keep a watch on your data assets and take timely measures in case of data anomalies. The observer monitors your selected data assets and provides alerts based on the selected observer rules.
  - Manage Observers
    You can manage your observers on the Observers page.
    - Create an Observer
      You can create multiple observers for a single data connection, but you cannot use the same assets across different observers. You must set up a successful data connection before creating an observer. To create a data connection, refer to DISuite/Observability/data-connections/Creating_Snowflake_Data_Connection.html.
      - Observer Rules
        Observations profile your data on a regular cadence. It observes and monitors your data to identify anomalies. Based on your selected observations, you will receive alerts for identified anomalies. You can use observer rules to generate trends that can help you to identify business impacts and take prompt actions.
        Volume Rule Configuration
        The data volume is defined by the number of rows in the data. The unexpected changes—addition or deletion of rows in the data, can impact the overall decision-making. Volume rule configuration helps to generate alerts for these unexpected changes.
        Data Drift Rule Configuration
        You can track a set of statistics for Numeric and Textual data such as Cardinality (number of distinct values), min/max values, min/max length, number of empty/blank values, new values found, and so on. The unexpected changes in the historical trends of any of these statistics can impact overall decision-making. Data drift configuration generates alerts for unexpected changes in the selected statistics. The alerts will be generated if the value of the selected statistics increases or decreases than its expected value.
        Confidence-based alerts
        Data Drift Statistics
    - Edit an Observer
    - Delete an Observer
  - Search Observers
    You can search for a specific observer.
  - Reference
    This section provides reference information for Observers.
- Alerts
  Alerts are generated as per the observer rules and the assets that are selected during observer creation. The alerts are either critical level or warning level. This level is set during the observer rule configuration.
Data Governance
Manage data policy and processes with greater insight into your data's meaning, lineage, and impact.
Data Quality
Assure reliability, consistency, and accuracy data from different sources to deliver value to employees and customers.
Administration
Manage your subscription, your users and their roles, and other system tasks.

Data Drift Rule Configuration

You can track a set of statistics for Numeric and Textual data such as Cardinality (number of distinct values), min/max values, min/max length, number of empty/blank values, new values found, and so on. The unexpected changes in the historical trends of any of these statistics can impact overall decision-making. Data drift configuration generates alerts for unexpected changes in the selected statistics. The alerts will be generated if the value of the selected statistics increases or decreases than its expected value.

The image below shows the graphical representation of data drift alert. The X-axis shows the period and Y-axis shows the maximum length statistic for CONTRACT_AMOUNT column. In this example, a critical alert is generated when there is a sudden rise in the maximum length statistic for CONTRACT_AMOUNT column from 1000 to 60000 over a period between September 18 and September 19.

Data Drift Alert — Figure 1. Representation of Data Drift alert

You can configure observer rule during observer creation.

To configure the data drift rule, click the configuration icon.

The data drift alert is set as:

Confidence-based alerts