Dimensional modeling: Difference between revisions

Revision as of 13:52, 23 August 2021

Revision as of 06:31, 1 September 2021

Line 58:

* Extensibility. Dimensional models are scalable and easily accommodate unexpected new data. Existing tables can be changed in place either by simply adding new data rows into the table or executing SQL alter table commands. No queries or applications that sit on top of the data warehouse need to be reprogrammed to accommodate changes. Old queries and applications continue to run without yielding different results. But in normalized models each modification should be considered carefully, because of the complex dependencies between database tables.

== Dimensional Modelsmodels, Hadoop, and Bigbig Datadata ==

{{NPOV section|date=June 2018}}

We still get the benefits of dimensional models on [[Apache Hadoop|Hadoop]] and similar [[big data]] frameworks. However, some features of Hadoop require us to slightly adapt the standard approach to dimensional modelling.{{cn|date=May 2019}}