Differentiating between a Corporate Information Factory (CIF) and a Business Dimensional Model (BDM) may come down to two different directions of strategic thought: top-down (CIF) or bottom-up (BDM).
In the BDM, otherwise known as the Kimball approach, data remain in their respective logical business units (e.g, Sales or Production) but are brought together into the data warehouse through a commonly defined bus architecture. This approach is most prevalent in the Microsoft BI stack. Star or snowflake schemas are utilized and data are rarely normalized past 1NF, if at all. The logical focus is on the originating business units and the goal is often to allow these units to more effectively share data across the organization. For presentation, fewer queries and joins are necessary than one would need to make sense of CIF data.
The CIF, or Inmon approach, starts with the central data repository as the unit of focus as opposed to the individual business units. The business units can create data marts from the normalized tables. Third normal form is required. The most apparent disadvantage here is the amount of time and thought required to implement a true CIF, but the resulting product is a true enterprise data factory. More joins are needed, though, to put the data into presentable form.
Where Extract-Transform-Load or Extract-Load-Transform is concerned, the former (ETL) is the most conventional understanding of the process and typically implemented in dimensional modeling. The transformation happens before the data reaches the target system and is logically arranged already—to some degree—by business until or purpose. The latter (ELT) is utilized most often in more powerful analytics implementations or data lakes.
References
Bethke, U. (2017, May 15). Dimensional modeling and Kimball data marts in the age of big data and Hadoop. Retrieved from https://sonra.io/2017/05/15/dimensional-modeling-and-kimball-data-marts-in-the-age-of-big-data-and-hadoop/
Harris, D. ETL vs. ELT: How to choose the best approach for your data warehouse. Retrieved from https://www.softwareadvice.com/resources/etl-vs-elt-for-your-data-warehouse/
Kajeepeta, S. (2010, Jun 7). Is it time to switch to ELT? Intelligent Enterprise – Online. Retrieved from https://proxy.cecybrary.com/login?url=https://search.proquest.com/docview/365390283?accountid=144789
Kumar, G. (2017, Mar 14). Dimensional modelling vs corporate information factory. Retrieved from http://www.data-design.org/blog/dimensional-modelling-vs-corporate-information-factory