WHITE PAPER:
The key enterprise risk management (ERM) issue for many financial institutions is to get enriched data in a single place in order to report on it. Learn best practices for data management that are critical for ERM.
WHITE PAPER:
Through data modeling of BI systems, we can meet many of today’s data challenges. Through logical and physical modeling of business intelligence systems, we can enable the delivery of the correct business information to business users. Read this paper to learn more.
WHITE PAPER:
This paper examines the business issues that drive organizations to consider a real-time change data capture solution to optimize ETL processes. This helps alleviate batch windows to enable the delivery of timely, trusted information to the business.
EGUIDE:
In this e-guide, learn how you can master SAP HANA for increased speed of development, speed of realization, flexibility, and more – for the maximum impact on your organization
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 on to find details about SAPs BusinessObjects Predictive Analysis, including how the NBA used HANA to help cater to stat-hungry fans.
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.
EBOOK:
This expert guide divulges essential information on how to use the newest sales tools for customer prospect generation; bolster sales forecasting with data modeling; use location-based apps; and more.
EGUIDE:
Surging big data is changing data modeling techniques and app development cycles. Read on to discover what you should expect from big data's near-future and best practices when it comes to transitioning big data applications into the production stage.
