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Business Intelligence: Using Data Effectively
Posted in: Uncategorized - Oct 07, 2010Your CEO is probably already pushing you to find effective ways to increase revenue through the services or solutions you already employ. Doing so is getting harder with each passing month as data piles up, products falter, and youre forced spend your time putting out fires. A recent study commissioned by Sybase and conducted by the University of Texas reveals that improving the overall intelligence and accessibility of data in your operation could do wonders for your bottom line. In fact, its possible that you could generate millions of dollars in additional revenue simply by improving the way your data works for you. The University of Texas study has found that a 10% improvement in data effectiveness can deliver significant ROI. The study was conducted by the university's McCombs School of Business in conjunction with the Indian School of Business. More than 150 respondents from Fortune 1000 firms completed the survey. Financial and some operational performance data on the firms represented by the survey respondents was collected from archived sources. The empirical analysis involved two steps: Factor analysis to determine distinct attributes of data, and multiple regression analysis to test the relationships between data attributes, controls and performance measures. - ...top
Sybase Survey Reveals Analytics Paradox
Posted in: Business Intelligence - Oct 06, 2010IT sees value of Analytics, but few have formalized analytics plan.top
Q&A: MDM Proving Its Value at Health Services Company
Posted in: Master Data Management - Oct 06, 2010MDM may not be easy but it's worth the effort.top
Q&A: MDM Proving Its Value at Health Services Company
Posted in: Master Data Management - Oct 06, 2010MDM may not be easy but it's worth the effort.top
Trusted Data for BI: Integrating Data for Success
Posted in: Business Intelligence - Sep 30, 2010Giving business and technical users data that they trust is key to good business intelligence (BI). If users don’t have confidence in the data of a data warehouse and other BI data stores, they may argue over the data’s accuracy, refuse to use the reports and analyses fed from the data, or build their own data stores.top
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