Core data and predicate on large volume

Hi,
In one of my current project requirement is to view product information in perticular date range.
Input
No. Of products :- P1 P2 P3 P4 P5
No of channels....:- C1 C2 C3 C4
No of regions :- R1 R2 R3 R4
Depending on any of the above combination user can select either "Daily" "Weekly" "Monthly" "Yearly"
for daily for Perticular date there will be (5 produtcts *4 channel*4 regions)= 80 Combinations
Daily :-so for 5 years it will be (80*365*5=1,46, 000) records
Montly:- for monthly for 5 years :- 12 *5 = 60 so total 4800 records.
quarterly for quarterly for 5 years :- 4 *5 = 20 so total (20*80) =1600 records.
That means we can calculate all daliy monthly , quarterly and yerly using daily data.
As user can varies the selected combination of product , channels and regions and can also slect the date range.
Looking at the search criteria , we decided to load the data into core data and then use predicate to fetch teh data.
Calculation formula:-
Day :- On perticular date
Weekly :- On friday i.e. end of week
Monthly :- 31/30 month end date
Quarterly :- March end date , Jun end date etc.
Yearly 31st dec date
But my questoion is ,
1.Can we use Daily model to fetch also monthly , quaterly and yearly information. Memory optimization good vs response time less
2. Sepaarte data model for Daily , Monthly and quarterly . Yearly we can calculate from quarterly . [Response time good but duplicate data]
Could anyone plesae suggest which is the best option to model this data ?

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