"Data, data everywhere, nor any byte to drink" is a paraphrase from the "Rime of the Ancient Mariner." This paraphrase depicts the agony of thirst while floating on an ocean of water. As businesses, we certainly float upon an ocean of data, little of which is information that truly improves our business.

Did you know that the world currently produces approximately two billion gigabytes (or two exabytes) of unique information per year? According to a University of California study, this is roughly 250 megabytes for each man, woman and child on earth.1 Printed material comprises only .003 percent of the total; in contrast, business information contained in personal workstations is by far the largest component.

Terabyte data warehouses are now common. Web site clickstream data is combined with call center data. Additionally, flows from external content providers are starting to pour into our warehouses. Two exabytes will be nothing in a few years!

David Shenk uses the analogy of data smog as the "noxious" information we breathe. In his book, Data Smog: Surviving the Information Glut, he writes, "Our information environment has become polluted... Just as fat has replaced starvation as this nation's number one dietary concern, information overload has replaced information scarcity as an important new emotional, social and political problem."

Business intelligence (BI) is often touted as the solution to data smog. Precision analyses cut through oceans of data to surface just the information we need to manage our businesses. Data warehouses filter and cleanse the smog produced by our transactional systems.

However, is BI really dispelling data smog? Or has BI also become a major polluter?

Microsoft recently announced XML for Analysis (XLMA), which is designed to discover and execute analysis services with open Web protocols (HTTP, XML, SOAP).2 It can be used across various platforms and developed using various programming environments.

XMLA is based upon Microsoft's OLE DB and Meta Data Services; therefore, XMLA is propriety. One should note that Sun, IBM and Oracle were not among the list of supporters. However, the object model is based on the open information model (OIM), developed by the Meta Data Coalition that is now merging with the Object Management Group. So, there is hope for interoperability and even the emergence of an industry-wide standard.

Could XMLA (or its equivalent) help us dispel some data smog? Consider the following:

First, XMLA permits thin- client tools to perform OLAP and data mining analyses. It minimizes client/server interactions by raising the level of functionality while maintaining a stateless dialogue for scalability. XMLA-based tools can be migrated from executive workstations to the shop floor and remote field offices using PDAs and Internet-enabled phones.

Second, XMLA permits sophisticated analyses to be embedded into operational applications. This greatly expands the range of people that can benefit from analyses by tailoring information to their specific jobs.

Finally, XMLA permits the beginning of an enterprise architecture that can manage the analytical infrastructure. The discovery method of XMLA can list available analysis resources and properties about those resources. The enterprise warehouse could be used to aggregate those analysis resources, thus presenting a single image of the enterprise analytical infrastructure. Further, XMLA is compatible with B2B exchange standards, such as universal description, discovery and integration (UDDI), so analysis resources could eventually be globally published.

It is apparent that XMLA (or its equivalent) is required to manage the complexity spawned by the explosion of BI applications. If there is any chance of dispelling data smog, we must have an effective BI strategy that focuses the proper analyses at the proper points within business processes. We must also have an enterprise analytical architecture to manage the complexity of that strategy.

In the last column, a revised definition for BI was offered. Simply put, if it does not change the way that you do business, then it is not BI. In this column, a further refinement is offered. If you cannot manage the BI infrastructure, then you will eventually have a big mess.

EMA's Take- Away

  • Get tough on what you will accept as information. Do not pollute! Ask whether the information will improve the way you do business. Will the information enable you to retain your profitable customers, hone distribution channels and streamline the supply chain?
  • Urge vendors to provide the architecture and tools to manage the enterprise infrastructure for BI. Adopting point solutions will solve short-term crises but will back you into a corner. Expend reasonable efforts to build a long-term BI infrastructure.

1. http://www.sims.berkeley.edu/how-much-info/
2. http://www.microsoft.com/data/

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