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.
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.
The construction of a data model is one of the more difficult tasks of software engineering and is often pivotal to the success or failure of a project. Many factors determine the effectiveness of a data model. In this white paper, industry expert Michael Blaha covers the Top 10 pitfalls to avoid — from both the strategy and detail perspective.
Oracle Business Intelligence Applications (OBIA) can give organizations deeper analytical views into their business performance. In this tip guide, readers will learn about five key areas organizations should focus on when implementing OBIA.
This presentation transcript features speaker Evan Levy, partner and co-founder of Baseline Consulting, a professional services firm concentrating on enterprise data issues. This discussion is about data quality and some of the challenges and pitfalls that are seen during data quality implementation.
The first key to a successful data governance program is ensuring user and organization expectations. To find out more secret advice for highly effective data governance programs read this expert e-Book. Our editorial team has gathered tips, techniques and best practices to plan a successful data governance plan.
Despite criticism of application development methodology over the years, some fundamental problems haven’t been addressed successfully. This paper examines a new direction supported by the IBM InfoSphere Foundation Tools. These tools provide a coordinated approach well-suited to the special needs of contemporary information-centric development.
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.