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Best Practice for Improving Data Anomolies

  • 23 February 2021
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I am trying to understand the best practice around limiting the number of Data Anomolies we have, specifically with the number of accounts with no customer info value. I know that it can occur with validation rule errors that impact Gainsight from updating the CustomerInfo field, but it is happening on a large number of accounts and then impacting the creating of new Relationships.

Besides going in and manually fixing each record is there a best practice around getting to the root of the problem so it lessens?

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Best answer by gopal_rao_kallepu 1 March 2021, 10:20

@kytpowell as you rightly said these kinds of data anamolies arise due to complex trigger flow and validation rules. We suggest you to review the validation rules and triggers on your Account object if the data anomalies are frequent. Please reach out to our support if the problem persists, to help us understand your org set up better.

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@kytpowell Thanks for sharing your query here. Its been long time I had hands-on this area. I will check on this and get back to you. 

Userlevel 3

@kytpowell as you rightly said these kinds of data anamolies arise due to complex trigger flow and validation rules. We suggest you to review the validation rules and triggers on your Account object if the data anomalies are frequent. Please reach out to our support if the problem persists, to help us understand your org set up better.

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