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In addition to increasing the price of deployment, setting up these datawarehouses and processors also impacted expensive IT labor resources. Robust dashboards can be easily implemented, allowing potential savings and profits to be quickly highlighted with simple slicing and dicing of the data.
Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.
Left to their own devices, they had resorted to using legacy reporting tools such as Excel that required manual gathering, slicing and dicing of data. Consequently, this data was siloed, unshareable, hard to use, lacked quality and governance controls, and could not be used in automated processes.
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