How do you handle situations where self-service users create analyses with incorrect conclusions or misleading data? How do you balance correcting errors with encouraging continued self-service usage?

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Quality issues in self-service analytics are inevitable and handling them well is critical. Overreact by restricting access and you kill the self-service program. Ignore errors and you erode data trust.

How do you handle situations where self-service users create analyses with incorrect conclusions or misleading data? How do you balance correcting errors with encouraging continued self-service usage?

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