Sentence examples for enterprise data warehouse from inspiring English sources
"They have this notion of one version of the truth, that nothing is of consequence unless it's in their enterprise data warehouse".
Recent projects include electricity demand forecasting in smart electric grids, enterprise data warehouse optimization in high-tech and telecom operations, and process automation in nuclear power plant operations.
Data Management and Reporting is the information technology application support group behind Stanford's reporting applications (ReportMart1, ReportMart2, OBIEE) and enterprise data warehouse.
The case is based upon real options analysis for an enterprise data warehouse (EDW) and analytic customer relationship management (CRM) program at a major U.S. firm.
This was the era of the enterprise data warehouse, used to capture information, and of business intelligence software, used to query and report it.
This study validated enterprise data warehouse (EDW) data for a cohort of hospitalized patients with a primary diagnosis of diabetic ketoacidosis (DKA).
Extract-transform-load (ETL) workflows model the population of enterprise data warehouses with information gathered from a large variety of heterogeneous data sources.
Agile methods for enterprise data warehousing (EDW) are rooted in the iterative programming techniques that teams use to build departmental-specific or other, single-sponsor business analytics systems.
Although enterprise data warehouses were initially intended to facilitate exploration and analysis, they have become production data repositories for many organizations, and, as previously noted, getting data into them is time-consuming.
At their root, agile data warehousing methods incorporate practices such as Scrum or Kanban to accelerate programming, but this strategy alone is not enough because poor software engineering practices in the phases leading up to or following application coding can fatally undermine an enterprise data warehousing (EDW) project.
A single vocabulary for EDW projects should draw from the definitions provided by professional organizations including DAMA, TDWI, and IEEE, and it will have to cover topics such as basic business terms, information services, software engineering, data architecture, enterprise data warehousing.
