EGUIDE:
Inside this expert e-guide, Johna Till Johnson explores the emerging world of User Behavioral Analytics (UBA) and how it can give you a clear view into what should, and what should not, be going on in your virtual environment. Inside you'll find a breakdown of the features a UBA provides, and a basic deployment plan to get your program running.
PRESENTATION TRANSCRIPT:
This Presentation Transcript, featuring Forrester Research, explains how Software as a Service business intelligence can deliver a more cost-effective way to get relevant information to those who need it faster than traditional business intelligence can.
VIDEO:
CA ARCserve Backup r12.5 uses a three-tier architecture within a domain. Check out this demonstration for an explanation of the CA ARCserve Backup r12.5 SRM Features, including architecture, dashboard overview, nodes and tiers, and SRM probe.
WHITE PAPER:
This white paper discusses: What is an industry model? What is the value of industry models? Considerations for building or buying data models IBM Industry Models—business and technical blueprints Reducing time to value with IBM Industry Models
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.
ANALYST REPORT:
Mobile business intelligence is a process, not a project, and a journey rather than a destination. The case studies included represent two forms that mobile BI can take to empower the mobile worker and port existing applications. This paper discusses two different companies, their environments, reasons for going mobile and key success factors.
WHITE PAPER:
This paper discusses how traditional BI systems with disconnected capabilities fall short at monitoring, aligning and benchmarking performance. Learn how Oracle BI 11g is designed to help today's organizations drive profitable growth, change, and many other operational and functional performance goals.
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.
