EGUIDE:
Building predictive models is a complex, time-consuming process that demands a lot of skill. This expert e-guide reveals key steps to develop and implement a successful predictive analytics initiative. Discover how you can monitor the accuracy of predictive models, identify ideal candidates for predictive analytics teams, and more.
WHITE PAPER:
Read this white paper and learn how the data warehouse, metadata and modeling environment will be transformed in the next few years — and what you need to do to leverage it for your business, the major components of DW 2.0 architectures, and key modeling and metadata management strategies for DW 2.0.
EGUIDE:
Business intelligence and predictive analytics have the potential to revolutionize the way CIOs make decisions and align IT with business goals. By collecting valuable data, CIOs can promote innovative change. Inside this exclusive e-guide, learn how New York City Housing Authority’s CIO used BI and predictive analytics to do just that.
WEBCAST:
Explore with William McKnight the factors involved and how organizations should go about valuing data quality through modeling and taking the right steps to remediate data quality defects throughout the enterprise.
PRESENTATION TRANSCRIPT:
Growing data volumes, diverging data sources, amplified information complexity, and increasingly varied users have made it difficult to take advantage of data as a true corporate asset. In this transcript featuring industry thought leader David Loshin, learn how to turn data complexity into an information advantage.
WHITE PAPER:
Whether or not analytics should become an integral part of an organization’s planning and decision-making seems to be beyond question However, at what level, for what purpose and how to go about deploying analytics are questions that each organization needs to answer for itself. These questions are the focus of this paper.
RESOURCE CENTER:
See how the SAP CRM Rapid Deployment Solution – helps organizations to get essential CRM capabilities, quickly at an affordable price and provides customers options to grow as their businesses grow
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.
