|
ARTICLES BY THE KIMBALL GROUP
DIMENSIONAL MODELING/DATA ARCHITECTURE Four Fixes Refurbish Legacy Data Warehouses DW/BI professionals are often tasked with making evolutionary upgrades and improvements to minimize cost and upheaval in the current analytic environment. We explore four upgrades that can breathe new life into legacy data warehouses. Kimball University: Integration for Real People These step-by-step guidelines will help dimension managers and users drill across disparate databases. Kimball University: Data Stewardship 101: First Step to Quality and Consistency Data stewards are the liaisons between business users and the data warehouse team, and they ensure consistent, accurate, well-documented and timely insight on resources and requirements. The Matrix: Revisited This Swiss Army knife for BI and data warehousing supports planning, integration and stewardship. Beware the Objection Removers Is that sales pitch flying in the face of conventional wisdom? Start asking questions now. Slowly Changing Dimensions Are Not Always as Easy as 1, 2, 3 The three fundamental techniques for changing dimension attributes are just the beginning. Fables and Facts Do you know the difference between dimensional modeling truth and fiction? Differences of Opinion Comparing the dominant approaches to enterprise data warehousing. Data Warehouse Dining Experience Managing a data warehouse is similar to running a restaurant. No Detail Too Small Although there's no substitute for atomic details, look into complementary consolidations. Fistful of Flaws Use this checklist to review your dimensional models. The Bottom-Up Misnomer Our data-warehousing approach is sometimes referred to as bottom-up, but it's far from it. Better Storytelling Dimensional design techniques bind events into stories The Soul of the Data Warehouse, Part 3: Handling Time The data warehouse takes a pledge to preserve history The Soul of the Data Warehouse, Part Two: Drilling Across Drilling across means asking for the same row headers from another fact table The Soul of the Data Warehouse, Part One: Drilling Down Drilling down just means "show me more detail" Declaring the Grain It's the most important dimensional design step after identifying data sources To Be or Not To Be Centralized Contrary to conventional data warehouse wisdom, physical centralization is not the question Fact Tables and Dimension Tables The logical foundation of dimensional modeling . Designing the Financial Data Warehouse Now that the finance function has knocked on your door, what's next? Divide and Conquer Build your data warehouse one piece at a time Two Powerful Ideas The foundations for modern data warehousing Design Constraints and Unavoidable Realities No design problem in school was this hard What Changed? Use a multivalued outrigger table to add expressive power to your dimensions Tricky Time Spans The time dimension isn't nearly as simple as it looks Wrangling Behavior Tags Behavior tags are true "text facts." How do we handle them in a data warehouse? Behavior: The Next Marquee Application It's time to start using more advanced analytics Realtime Partitions Build a special extension of each fact table to complement your static data warehouse Lost, Shrunken, And Collapsed Why and how to create the three types of aggregates in a dimensional data warehouse |
 |
Most Popular This Week
IE Weekly Newsletter
Subscribe to the newsletter
| |
| |||||||||||||||||||||||||||||||
