article thumbnail

Common Business Intelligence Challenges Facing Entrepreneurs

datapine

In addition to increasing the price of deployment, setting up these data warehouses 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.

article thumbnail

How OLAP and AI can enable better business

IBM Big Data Hub

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.

OLAP 60
article thumbnail

How Newcomp Analytics partners with IBM to advance clients’ supply chain insights

IBM Big Data Hub

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.