Tutorial: backfilling analytics data with RudderStack

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In an ideal world, you would never have to backfill data due to outages or migrations. For data engineers in the real world, though, backfilling data is inevitable.

Even if something doesn’t break, APIs can hit limits and downstream teams often want to change the tools they are using…and that means backfilling data.

We recently had to do this ourselves. The marketing team wanted to onboard a new analytics tool, but they also wanted 6 months of historical data in that analytics tool from the start. Normally that would require a ton of painful work on pipelines and load jobs, but in our case, it was easy because we were using…you guessed it: RudderStack! Well, that and we had a copy of the raw data in our warehouse.

Here’s a high level overview of how we backfilled 6 months of data and got the marketing team up and running in less than a day:

Determine the tables in Snowflake that need to be loaded (which for us were the standard identify, track and page tables)

Create a staging table in Snowflake with the combined data set

Adjust payloads as needed with a RudderStack User Transformation

Create a RudderStack Reverse ETL pipeline and send the events

Check out this step-by-step guide, which includes a code sample of the RudderStack User Transformation we wrote.

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