Hi All
Is anyone out there pulling large detail data into their QV models , by this I mean more that 350 Million rows of data, a good
example would be sales data at a granularity of second [time stamp].
I'm interested to know how to build an optimized data model with the above data, which approach is best to handle the decent reloads on this data.
ex: I have more than 45 fields in the table , in those 5 fields are having metric information, then in the remaining
remaining fields 23 fields I am using as dimensions in the qv app.
this table has rows more than 350 Million records for each year.
I would like to see the data up to half an Hour level [30 min] ,[aggregate data to 30 min] .
how can I achieve it in data model.
I'm interested in hearing about your stories here. Particularly and tips and tricks for performance.
I have read so many whitepapers on Best Practice model design, However I am expecting an experienced solution for this.
Many thanks in advance
John
