What This Document Is
This document is an in-depth exploration of multidimensional database technology, originally published in *Computer* magazine. It delves into the core principles behind these databases, contrasting them with traditional relational models. The material examines how multidimensional databases are structured to facilitate complex data analysis and decision-making, moving beyond simple transaction processing. It’s a focused look at a specific approach to database management geared towards analytical applications.
Why This Document Matters
This resource is valuable for students and professionals in computer science, data science, and information systems who are seeking a foundational understanding of multidimensional databases. It’s particularly relevant for those studying data warehousing, Online Analytical Processing (OLAP), and data mining. Anyone looking to understand the historical development and theoretical underpinnings of these technologies will find this a useful read. It’s ideal for supplementing coursework or for researchers investigating advanced database architectures.
Common Limitations or Challenges
This document provides a conceptual overview and historical context. It does *not* offer practical, step-by-step instructions for implementing a multidimensional database system. It also doesn’t cover specific software packages or current implementations in detail. The focus is on the underlying principles and evolution of the technology, rather than a “how-to” guide. It assumes a baseline understanding of database concepts.
What This Document Provides
* A comparison of multidimensional databases with relational databases and spreadsheets.
* An overview of key application areas for multidimensional data models, including data warehousing and OLAP.
* Discussion of the historical development of the multidimensional data model.
* An exploration of how data is categorized within multidimensional databases (facts, measures, and dimensions).
* Insights into the challenges of using traditional SQL for complex analytical queries.
