Sept. 27 2009 12:00 AM

The Importance of Integrity and Flexibility

 

Imagine the scenario where the CIO reviews the long-term goals of the IT organization and outlines an initiative to develop business intelligence (BI) architecture for the enterprise. Often this is dictated by business needs - presentation of pertinent data to make informed business decisions in a multitude of applications. Identifying the best BI architecture for a particular organization requires a balance of pragmatism and idealism. There are philosophies that argue many sides of the BI equation, whether it be an open or closed vendor system, keeping it vendor agnostic, etc. However to have a successful BI architecture, the IT organization must understand the objective of the BI implementation, i.e. what a successful BI architecture achieves.

In choosing the right BI architecture, there are key considerations the organization should review, including flexibility and integration of legacy databases. Companies should look for solutions that have the potential for a departmental implementation to expand to an enterprise. Enterprise solutions typically have multiple database layers (data warehouses or staging layers) that separate the integration layer of the data from the analytical layer. Separating the data layers for integration and reporting allows each layer to be designed appropriately based on its usage and provides more flexibility as business requirements are added or change over time.

The reality of most IT infrastructures is that there are multiple legacy data warehouses with incompatible data. Managing legacy databases into a data integration layer may be difficult. Rather than recreating a legacy database, data may be reacquired utilizing an integrity solution. That integrity solution can be utilized for reporting purposes and verifying the data already captured.

Separating the data and integration layers from reporting enables the organization to participate in an open system. Open systems offer the opportunity to be vendor-agnostic and leverage the infrastructure already in place. As organizations are unique and have varied data and reporting constructs, open systems allow for the creativity to have a BI architecture that is right for your organization.

RIMA FRANKLIN is the corporate director of strategy and planning at BÖWE BELL + HOWELL.

 



Better Self-knowledge Means Better BI

 

According to Wikipedia, business intelligence refers to skills, technologies, applications and practices used to help a business acquire a better understanding of its commercial context. BI achieves its purpose by concentrating on records, statistics and business objectives to improve tactical and strategic planning and decision-making.

When used effectively, business intelligence can help an enterprise better understand its clients and improve customer service, optimize supply chain management, more rapidly uncover both problems and opportunities and, ultimately, create or maintain a strategic advantage. A typical BI architecture features a data warehouse, staging databases, data mining online analytical processing (OLAP) and business modeling capabilities.

Because BI is in its formative stages, its architecture or terminology is not yet consistently defined, which frequently makes designing and implementing a BI system difficult. Off-the-shelf applications may use underlying concepts and definitions that differ from those used by a given business in its particular applications. For example, Company A might define "customer" to mean all current and past customers plus prospects, while with Company B, "customer" might refer only to those buyers who bought a product or service over the past year. Still yet another company might differentiate between new customers and clients. Hence, the defined set of customers in Company A's database will differ in kind from that of Company B's, and so on. Obviously, such discrepancies in grouping data can create sticky problems when it comes to analysis - problems that can be solved through the proper application of data warehousing tools.

On the lighter side, Data-Warehouses.net tells how a shopping market chain's data mining techniques determined that the wives of new fathers often asked them to buy diapers on the way home from work, and those husbands often bought beer or wine on the same trip. By displaying the alcoholic beverages next to the diapers, the retailer sold more diapers and more liquor!

An old adage says, "If you don't know where you're going, you'll wind up somewhere else." Needless to say, choosing the incorrect BI architecture could have long-term, detrimental implications to an enterprise, so it bodes well for an organization to choose its BI system wisely.

CHARLES JENSEN is an associate of IMERGE Consulting, a document-centric management consulting firm.