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If you have been managing Power Platform environments for any amount of time, you probably know how this goes. A user calls you to say their app is not opening, or someone from the business tells you a critical flow has been failing since yesterday morning. You are the last one to find out. That…
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This post explains elastic tables in Dataverse, highlighting their structure, creation process, and key considerations. Unlike standard tables, elastic tables, backed by Azure Cosmos DB, support high volumes of semi-structured data and automatic scaling. They are ideal for unstructured data but lack transactional integrity typical of relational databases.
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The Dataverse Attribute Dependency Scanner is a cloud flow that helps administrators identify which cloud flows reference specific Dataverse columns before renaming or deleting them. Triggered via a Teams channel message, it automates the search for flow dependencies, making it easier to manage schema changes without unexpected failures during production.
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