WHITE PAPER:
Sybase IQ is a market-leading analytics server which enables organizations to perform deep analysis of massive amounts of data, accessed by multiple users requiring answers in real time.
WHITE PAPER:
This paper highlights the performance and scalability potential of InfoSphere DataStage 8.1 based on a benchmark test simulating a data warehouse scenario. The benchmark is designed to use the profiled situation to provide insight about how InfoSphere DataStage addresses customers' key FAQs when designing their information integration architecture.
WHITE PAPER:
Learn how Data Modeling supports cloud computing since interaction among the Cloud Service Provider, Cloud Administration and Customer needs to include a well thought out data architecture before a DBMS designed offering in cloud computing is deployed. Continue reading to learn more.
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:
Uncertainty makes strategic planning complex. Removing uncertainty can create unlimited business value. There are solutions to help organizations overcome uncertainty and achieve results. Read this white paper to learn how to drive strategic planning with predictive modeling.
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:
Often times Business Intelligence (BI) projects miss the mark with their business users because the proper documenting of required data and related business rules is not executed. This paper looks at fast-tracking data warehousing and BI projects using data modeling.
WHITE PAPER:
This white paper describes how IBM's Information Server FastTrack accelerates the translation of business requirements into data integration projects. Data integration projects require collaboration across analysts, data modelers and developers.
