#PowerPlatformTip 81 – ‘Fast DataSource Updates’

💡 Challenge

You have a large data set in a data source (it could be SharePoint, SQL, or any other data source), and you need to update a significant portion of it. Using UpdateIf directly on the data source is not efficient and can take a long time to process.

✅ Solution

Combine ClearCollect, UpdateIf on a local collection, and Patch to perform efficient bulk updates to the data source.

🔧 How It’s Done

Here’s how to do it:

1. ClearCollect a local collection from the data source.
   🔸 Use ClearCollect(LocalCollection, DataSource) to load up to 500-2000 items into a local collection.
   🔸 Note: By default, ClearCollect has a limit of 500-2000 items based on your app settings.
2. Update the local collection.
   🔸 Use UpdateIf(LocalCollection, Condition, Changes) to apply your changes locally.
   🔸 Modify or transform only the records you need before sending them back.
3. Patch back to the data source.
   🔸 Use Patch(DataSource, LocalCollection) to update the original data source with the modified collection.
   🔸 This batch update is much faster than updating each record directly.

🎉 Result

You can efficiently update a large number of items in any data source without hitting performance bottlenecks.

🌟 Key Advantages

🔸 Speed – faster than using UpdateIf directly on the data source.
🔸 Flexibility – perform complex updates on the local collection before patching.
🔸 Scalability – handle large data sets efficiently, especially when extending item limits.

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🎥 Video Tutorial

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🛠️ FAQ

1. What is the purpose of ClearCollect in this method?
ClearCollect creates a local collection of records from your data source, allowing you to perform updates locally without repeatedly calling the data source.

2. Why shouldn’t I use UpdateIf directly on the data source?
Using UpdateIf on the server-side data source is slower and can hit performance limits when processing large data sets.

3. How can I work around the default item limit of 500–2000 records?
You can use ForAll in combination with Collect to fetch and process records in batches, circumventing the default delegation limit.