News

Too Many Companies Don’t Trust Their Data

Posted in: Uncategorized - Dec 16, 2016

Most professionals who work closely with data analytics are not confident in the integrity and reliability of resulting insights and worry about data quality. top

Emerging Design Patterns for Data Management

Posted in: Master Data Management - Nov 16, 2016

Organizations that seek to be data-driven are experiencing considerable change of late, because data itself, the management of data, and the ways businesses leverage data are all evolving at accelerated rates. These changes sound like problems, but they are actually opportunities for organizations that can embrace new big data, implement new design patterns and platforms for data, scale to greater volumes and processing loads, and react accordingly via analytics for organizational advantage.top

Why Users Don’t Connect to New Analytics Tools

Posted in: Uncategorized - Nov 07, 2016

IT leaders must come up with more user-friendly solutions that connect within preferred business apps in order to drive more interest in analytics tools.top

Ten Mistakes to Avoid When Defining an Enterprise BI and Analytics Strategy

Posted in: Business Intelligence - Nov 03, 2016

 

By Nancy Williams and Steve Williams

The benefits of business intelligence—and now big data analytics—may be couched in different business terms, but there has to be a connection to increased profits if there is to be a return on a BI investment. This Ten Mistakes to Avoid examines some of the key, commonly encountered BI strategy challenges faced by major companies across a wide range of industries.

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Dynamic Metadata: Enabling Modern BI Architecture

Posted in: Business Intelligence - Nov 02, 2016

In a highly competitive market, today’s forward-looking organizations are seeking to optimize and modernize their IT investments, specifically in enterprise business intelligence (BI). There’s a strong push to capitalize on newer features such as self-service BI, advanced analytics, and customized visualizations—all of which relinquish the centralized data governance necessary for corporate and regulatory compliance. top

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