Justifying The Value of OLAP

So I was in this meeting at a client site yesterday, we talked about the progress of their DW upgrade and the dashboard/scorecard implementation that my consulting firm is tasked to do.  During our discussion, one of the IT folks, actually a contractor indicated that the current DW (SQL Server 2000) hasn't an OLAP layer, namely cubes.  All user reporting needs are satisfied through the relational DW database.  As part of his assessment, he is putting together a series of proof-of-concept cubes based upon the data sitting in the current DW.  Everything sounded good until we got further into our meeting and the following points were made by the other participants.

• Performance with reporting is not an issue. 
• All canned reports are created in Excel and are being pushed directly to the users.
• All users are "causal."  There are no "power" user requirements such as more complex analysis or ad-hoc query.
• No one in-house knows anything about cubes or multi-dimensional concept.

My inclination here is to ask, at least in the back of my mind, how much value the OLAP layer provides in this scenario.  I can see the POC as showcasing the potential value the OLAP layer may offer in the distance future. Other than that, we are adding a whole new layer of technology to the DW framework which requires additional skill sets and resources to support and maintain.  I maybe missing a bigger picture here but I am not seeing the ROI on this endeavor.

Describing a Data Warehouse

While I was on a sales call yesterday I found myself explaining away what a data warehouse is.  Honestly I was in some way caught off guard by the question.  I shouldn't have been but I guess I haven't had to do such in a while.  Or maybe I thought that data warehousing has been around for "so long" I presumed everybody would somehow know about it.  This is undoubtedly a bad assumption on my part. 

Nonetheless it was a refreshing surprise.  It is not exactly easy to answer the question of what is a data warehouse.  I wanted to be "accurate" and provide a portrayal that is both "textbook" and draws from my own account over the years. 

I believe the essence of a data warehouse is data consistency and non-volatility.  A data warehouse is an integration of information gathered from different operational applications and other data sources used to support business analysis activities and decision-making tasks. It captures an organization’s past transactional and operational information and changes. The data in the warehouse, in most cases, is read-only. Unlike OLTP systems, the architecture (and the technologies) of a data warehouse is optimized to favor efficient data analysis and reporting.

I suppose my view of a data warehouse, in many ways, aligns with Inmon’s top-down approach. But that certainly does not preclude me from also seeing it as a collection of more subject-oriented data marts – Kimball’s bottom-up approach.