Slowly Changing Dimension

Thank you for the contribution. I have a different scenario that I am wondering how to handle with Sisense.

I have something that changes state over time.  

for example a  Request goes through several states:  Received, Scheduled, In process, etc. Complete.

There are thousands of Requests per day. They typically go through their status changes over several days.

Want to report on amount of Request by Status and compare the current state/volume to history and forecast trends.  

Granularity might be daily or hourly data.

How do we build the data model and then query it to get aggregate counts at a specific date/time and look at the values preceeding (or following) that point? For example How many requests were "In Process" by hour between 3/1 and 3/5?  How does that compare to prior month or year?

The data doesn't change much so it seems like a mistake to populate / snaphot the Status for each time period (day, hour).  

But without that I don't know how to allow a user to select a date using the built in Dashboard filter and get data using effective dated dimmension. 

https://www.red-gate.com/simple-talk/databases/sql-server/bi-sql-server/clarifying-data-warehouse-design-with-historical-dimensions/