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This chapter focuses on data warehouse data model tuning techniques.
The WHIPS project (WareHousing Project at Stanford) which is developing algorithms for incrementally maintaining views in the data warehouse.
In a field study to explore influences on data warehouse refresh policies, we interviewed data warehouse administrators from 13 organizations about data warehouse details and organizational background.
But the data warehouse was hand-crafted.
Use the same core criteria to evaluate data warehouse appliances as traditional data warehouse approaches.
No need for a data warehouse.
Secondly, load the massive substation data into Hive data warehouse.
Investigators can search for samples using our i2b2 data warehouse.
The second thing is commitment to enterprise data warehouse technologies.
Demand that data warehouse appliance vendors back up their claims.
So we've recently introduced a data warehouse capability.
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