What is the name of the organization you are focusing on?

Posted: July 14th, 2022

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One of the furious debates in the field of data warehousing pertains to the DW planning and development approach. The two “forefathers” of data warehousing, Bill Inmon and Ralph Kimball have different takes on the process (also known as the “Inmon vs. Kimball” debate). Here is a short summary of their views:
(1) Top-down approach (The Inmon’s approach – not in the textbook we use)
DW is developed based on a complete Enterprise wide data model- i.e., need to consider all potential dimensions, data sources, etc. and integrate disparate data sources. DW is a single large organizational repository that feeds data into departmental data marts
(2) Bottom-up approach (The Kimball’s approach – the one the textbook we use emphasizes)
Starts with one data mart (e.g. sales); later on additional data marts are added (ex. Human resources, marketing, etc.). A “bus” of integrated data marts comprises the DW. Data flows from source into data marts, and only then potentially into an integrated data warehouse (The combination of data marts themselves may be considered a data-warehouse).
There are obviously advantages and disadvantages to each approach, pertaining to issues such as ease of data integration, feasibility, time-to-market, support, security, etc.
1. Please address the following points in a post:
Consider the organization you work (worked) in, or an organization you are familiar with. Assume that you are asked to develop a data warehouse that covers several processes (and caters to several departments) for this organization.
– What is the name of the organization you are focusing on? what do they do? (very short descriiption)
– Which approach would you recommend (Kimball, Inmon, or other, p.s. there are other approaches such as the “federated architecture”)?
– Why? please elaborate. i.e., why the selected approach is a better fit to the characteristics/ environment of the organization you chose. Consider a range of issues (e.g., ease of data integration, feasibility, top management support, time-to-market, cost, security, etc.)

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