I just published another post on Data on the Rocks, a superblog with writers from around the world sharing their knowledge about the Qlik ecosystem.
Generating snapshots without loops (Data on the Rocks)
This post details two methods for turning transactional Snowflake query history (one row per query) into snapshots of what queries are active each second in Qlik's load script: using a loop and using IntervalMatch.
Two related examples of concurrency use cases are analyzing Qlik session and reload data, ex., what else was running that may have caused a file conflict and reload failure? A logically similar solution is using slowly changing dimensions with start/end dates or times to generate snapshots of employee or product data for headcount or product mix.
For the Snowflake query history, this alternative data structure enabled us to generate insights about available capacity before consuming more credits and the effect of concurrency on query performance that were not possible with the raw data.
Details and a sample solution with data can be found in the linked post.