Portals eNewsletters Web Seminars dataWarehouse.com DM Review Magazine
DM Review | Covering Business Intelligence, Integration & Analytics
   Covering Business Intelligence, Integration & Analytics Advanced Search

View all Portals

Scheduled Events

White Paper Library
Research Papers

View Job Listings
Post a job


DM Review Home
Current Magazine Issue
Magazine Archives
Online Columnists
Ask the Experts
Industry News
Search DM Review

Buyer's Guide
Industry Events Calendar
Monthly Product Guides
Software Demo Lab
Vendor Listings

About Us
Press Releases
Advertising/Media Kit
Magazine Subscriptions
Editorial Calendar
Contact Us
Customer Service

Beyond the Data Warehouse:
How Business Affects the Technology

online columnist John Ladley     Column published in DMReview.com
July 19, 2002
  By John Ladley

After one of these articles comes out, a burst of e-mails agreeing wholeheartedly with everything that has been said quickly materialize. (Tongue firmly in cheek here.) Such was the case last month when the importance of business sustaining information was emphasized over a specific architecture. To review, there is no one "good" architecture or framework (you know, federated, atomic DW, etc.). Business needs must drive the appropriate framework. The design technique must be apolitical (not favoring a business group) and agnostic (not favoring a particular approach or framework).

The nature of most of the e-mail I received was to provide a bit more detail on the agnostic and apolitical approach. Therefore, we'll explore how the intrinsic nature of business information usage provides the clues to the "correct" framework.

Attributes of Information Usage

If information is not used, it is a wasted asset. When a business intelligence (BI) project is initiated with the reason given as "better access to data," what the business really is saying is saying is that they aren't using information. It is there, but not used. Therefore, the first step to being apolitical is to take a broad-spectrum look at the enterprise requirement to use information. Even if a CRM project office or a finance vice president sponsors the BI project, it is key that some type of big picture be examined.

Examining enterprise usage is not too hard and does not require permission for some type of controversial enterprise analysis effort. Figure 1 illustrates a simple example of mapping business drivers to standard usages of information. The enterprise big picture will vary based on business drivers and industry context.

Usage is manifested in achieving objectives. The BI environment supports this through supporting and providing metrics and other information requirements. If you examine some generic business drivers and cross-reference them with generic information uses, it is easily seen that the type of business use of data generates situations where a measure (in italics in Figure 1) is used to fulfill a business goal. This is actionable use of information.

Figure 1: Mapping Business Drivers

Once a set of measures has been developed, the attributes of the measures are used to formulate the requirements for the framework. By attributes, I mean the various descriptors of what makes up a measurement. Figure 2 lists a subset of the ones I use when developing technical requirements. The attributes are scored on a relative scale of your choosing. Figure 3 shows an example using our three metrics from Figure 1. Once the measures have been scored, it becomes apparent how the characteristics of that measure and its context for use shape the BI framework that will support that measure. It is obvious that a blended set of data structures or frameworks would be required to efficiently support an enterprise spectrum of measures.

If it isn't obvious, you can use a simple graph to show the distinctions between the different types of structures.

Figure 2: Subset of Technical Requirements

If we plot the various values from Figure 3 on a simple radar chart, we can see the obvious differences between the measures. Extrapolate this to several dozen measures, and you can see how measures of common characteristics can be identified. This way the most efficient framework can be created to deliver the measurement to the end user but within the scope of a master architecture that will be developed to support all measures.

Figure 3: Measurement and Scoring Matrix

If we look at a set of 50 or so measures, we may see the need for atomic data and summarized data. This means the architecture must support a central DW and a mart to be most efficient.

Once all measures are considered, specific projects can be rolled out to support subsets of the measurement, The development team can correlate the framework requirements to the applications to identify a series of iterations to implement new BI applications. As a bonus, the team can use the measures to identify ROI opportunities and build the business case.

Figure 4: Mapping Characteristics


The bottom line is that different structures are more efficient at meeting different needs. Different data "topologies" are required for different attributes. The essence of the entire exercise is to balance long-term total cost of ownership against business requirements. This gives the sustainable return on the DW investment.  The data warehouse staff must eschew the search for the one ultimate answer to their framework and apply sound analysis.

Figure 5: Data Topologies


For more information on related topics visit the following related portals...
DW Administration, Mgmt., Performance and DW Design, Methodology.

When John is not writing poetry as a hobby, he is a director for Navigant Consulting, which recently acquired KI Solutions, a management consulting firm specializing in knowledge and information asset management and strategic business intelligence planning and delivery. Ladley is an internationally recognized speaker and, more importantly, hands-on practitioner, of information and knowledge management solutions. He can be reached at jladley@navigantconsulting.com. Comments, ideas, questions and corroborating or contradictory examples are welcomed.

Solutions Marketplace
Provided by IndustryBrains

Data Validation Tools: FREE Trial
Protect against fraud, waste and excess marketing costs by cleaning your customer database of inaccurate, incomplete or undeliverable addresses. Add on phone check, name parsing and geo-coding as needed. FREE trial of Data Quality dev tools here.

Speed Databases 2500% - World's Fastest Storage
Faster databases support more concurrent users and handle more simultaneous transactions. Register for FREE whitepaper, Increase Application Performance With Solid State Disk. Texas Memory Systems - makers of the World's Fastest Storage

Manage Data Center from Virtually Anywhere!
Learn how SecureLinx remote IT management products can quickly and easily give you the ability to securely manage data center equipment (servers, switches, routers, telecom equipment) from anywhere, at any time... even if the network is down.

Design Databases with ER/Studio: Free Trial
ER/Studio delivers next-generation data modeling. Multiple, distinct physical models based on a single logical model give you the tools you need to manage complex database environments and critical metadata in an intuitive user interface.

Free EII Buyer's Guide
Understand EII - Trends. Tech. Apps. Calculate ROI. Download Now.

Click here to advertise in this space

E-mail This Column E-Mail This Column
Printer Friendly Version Printer-Friendly Version
Related Content Related Content
Request Reprints Request Reprints
Site Map Terms of Use Privacy Policy
SourceMedia (c) 2006 DM Review and SourceMedia, Inc. All rights reserved.
SourceMedia is an Investcorp company.
Use, duplication, or sale of this service, or data contained herein, is strictly prohibited.