WHITE PAPER:
This White Paper explores how traditional approaches fall short, what the automated solution and its benefits look like, how the on-demand delivery model best represents the integrated stack necessary for automation, and how the automated, on-demand model brings the benefits of BI to a far broader audience than ever before.
WHITE PAPER:
Reporting is recognized as a way for companies to improve service, ensure quality, control costs, and prevent losses by empowering decision-makers throughout the organization. This paper will explain why reporting is one form of business intelligence that has become business-critical.
WHITE PAPER:
Read this brief paper to learn about a platform that offers end-to-end visibility while transactions are in process. Learn how a customizable, operational dashboard enables real-time visibility into the overall state of operations and transactions across disparate systems and applications.
WHITE PAPER:
Metastorm BPM empowers knowledge workers, managers, and executives to contribute to enterprise success in measurable ways. Click here to learn how Metastorm BPM helps organizations achieve Enterprise Process Advantage.
WHITE PAPER:
This article explains in detail about how to arrive at and implement an effective business intelligence strategy, using both a BICC and performance management technology.
WHITE PAPER:
Use insight produced through analytics to improve performance and gain a strategic advantage. Learn how you can employ an enterprise-wide approach for maintaining data and using analytics for improved decision making.
WHITE PAPER:
This white paper from IBM describes how a set of five predictive imperatives can help ensure that your company maximizes the value of its customer relationships and sustains higher levels of revenues and profits.
WHITE PAPER:
We can define an effective marketing dashboard as one that enables marketers to visually display relevant and current campaign, customer, advertising and/or branding information needed to achieve marketing objectives.
WHITE PAPER:
In the following paper, we briefly describe, and illustrate from examples, what we believe are the “Top 10” mistakes of data mining, in terms of frequency and seriousness. Most are basic, though a few are subtle. All have, when undetected, left analysts worse off than if they’d never looked at their data.
