There are tones of material available in metalink about how to improve the performance of the Pricing engine, so I am not going into details, I will just high light some of those approaches.
- As all of us knows that Volume of data always Impact the performance, but that doesn’t mean we stop adding the data in the system, but when ever we define the Rules/Qualifiers/Attribute in the system, just take the long team approach and not short team, point that I want to make here is don’t define Qualifiers based based on the Individual records like Item/Customer/Address if possible define in terms of Category/Class/type etc.But many a time business need is to define in terms if Individual records , so that’s fine.
- Make sure you have an Archive/Purging Strategy in place. Almost every companies have seasonal Price list /Promotions/Qualifiers etc and these are required only for particular time in a year(s) , so when ever you feel some data is obsolete and not required any more , Archive/Purge it.
- Profile option – Profile options are very goods, Please make sure that you have set the Profile option properly, like
are set properly ,Similarly have a close look to profile options related to Blind Modifiers/ Pricing at
Scheduling/Build Attribute Mapping etc.
- Qualifier Strategy – Qualifier are always key in QP, make sure you have not define excessive qualifiers in the system.
- Make sure you execute below concurrent Program when every you define any Attribute Mapping or when ever you notice degradation in performance1
- Build Attribute Mapping Rules
- QP: Maintains the denormalized data in QP Qualifiers
- Patches - Stay on the top latest patches provided by Oracle ( BUT but this is not always a case and we can’t afford to apply each and every patch BECAUSE lots of testing efforts are required once you apply the patch), but do review the patch provide by oracle and try to in touch with the other folks in the industry who has already implemented the patches in their system.
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