Best practices for data hygiene in Totango

Practice regular maintenance within Totango to ensure your workflows run smoothly and that your teams make confident data-driven decisions. Here are some recommendations.

System access

Limit system access to authorized users. When an employee leaves, ensure prompt disabling of access to Totango—either manually or via Okta integration.
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User permissions

Implement role-based permissions, account assignment, and data visibility within attributes to ensure that only those who need access to data can view or modify. A common area to review is the ability to bulk edit within segmentsit's recommended that you restrict this permission to team admins, or those with proper training.
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Integration notifications

Implement automated notifications to identify anomalies and errors with data integration activity. Proactive monitoring helps you address issues promptly.
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Data validation

Whenever possible, add validation checks during data entry and ingest to ensure only accurate and complete data enters into the system, such as:

  • When creating rapid insight forms, ensure you mark relevant attributes as mandatory to ensure your teams complete necessary data prior to entering it into the system.
  • When creating attributes, ensure you use the right data type and format (if applicable). Lists and Multi-Select List types help to eliminate errors in data entry when left to text.
  • Create segments whenever introducing new attributes to ensure data values are being updated appropriately.
  • Leverage the preview button whenever editing a health profile or custom metric prior to applying changes. 

Data auditing

Conduct periodic data audits to review quality, accuracy, and compliance with established standards. Depending on your bandwidth, try to do an audit monthly. Within the data 360 SuccessBLOC, create scorecard KPIs to give you visibility into missing or inaccurate data that needs to be fixed.
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Data cleansing

Periodically remove duplicate records, correct inaccuracies, and update outdated information. This effort can be done through automated scripts or manual review. For correcting data in bulk, consider the power of local file uploads! 
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Naming conventions

Establish data standards for attributes, dimensions, custom metrics, integration jobs, assets, and more. Consistent data formatting reduces errors and ensures that your team can identify items with confidence. Always add a description when creating an attribute so your team can hover over the attribute and better understand the data context.
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Data governance

Assign responsibilities for data management tasks. This ensures that data ownership, accountability, and stewardship are clearly defined. Consider adding a process for your team members to submit requests that you and other Totango admins can consolidate and review (e.g., Slack channel).
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Data documentation

Maintain comprehensive documentation about your data sources, transformations, and processes. This documentation helps new team members understand the data and its context. Consider adding documentation as assets within a SuccessBLOC.
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Training and awareness

Train your team about the importance of data hygiene and specific practices they should follow. After all, your team's consistent efforts at the input helps drive the output! Their data entry powers much of Totango's automation. For example, the flow they add to a customer touchpoint may influence their health profile, which may be part of a larger program goal for renewalit's all connected!
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