When to Assess the Data Warehouse

　　Certainly any data warehousing initiative that is just beginning will benefit from a rigorous and comprehensive assessment. The results of such an assessment provide extensive information to position the initiative for success. Information about past efforts and current warehousing deployments describe the point at which the initiative is to begin. Information about business needs for, and expectations of, the warehouse describe the desired ending point of the effort. Assessment of the technical and organizational environments in which it will operate help to integrate the warehouse into existing business and IT processes. And understanding the readiness of the organization to build, operate, and use a warehouse, helps to plan the development and deployment projects.

　　Data warehousing assessment, however, is beyond the early stages. As needs, technologies, and environments change, reassessment has value throughout the life of the data warehouse. Assessment techniques can be effectively applied to data warehouses in various stages of maturity and completeness. A well-structured assessment is appropriate at any point where warehouse value and direction are uncertain, or at any time that the existing approach and infrastructure have become problematic. Typical times that a maturing data warehouse may benefit from reassessment include:

　　Revitalize an existing data warehouse – The data warehouse functions, but use and returned business value are lagging.

　　Make a transition from warehouse “builders” to warehouse “operators” – The warehousing organization needs to ensure ongoing data quality, enhancement and evolution in parallel with changing business needs, continuous management of a sound technical infrastructure, and continuously effective delivery of business information.

　　Move from “first generation” to “second generation” warehousing – The warehouse needs to migrate from loosely structured pooling of data to an improved structure with high levels of data integration, data accessibility, and customized information delivery.

　　Position warehousing as a core technology, and extend their leading edge to include knowledge management.

　　In these situations, or at any time when information is needed to increase or sustain the business value of the warehouse, assessment is the right approach. Clearly, then, data warehouse assessment is not a one-time event. Any of the situations just described may apply to a single warehouse at different points of implementation and maturity. Data warehousing represents a long-term commitment, and a key business enabler. Sustained value – given that the warehouse is deployed within a continuously changing landscape of technology, organizational structure, business priorities, and marketplace realities – demands a warehouse that evolves and adapts. Periodic assessment of the data warehouse may be necessary to ensure continued health, vitality, and value.

　　The Opportunities and the Challenges

　　Defining a successful data warehouse assessment approach, and using it effectively, require an understanding of the opportunities and challenges that a typical data warehouse may include. Although they vary widely in size and scope, data warehouses in general represent large and complex solutions to data integration and delivery problems. A typical data warehouse is challenged to:

　　Extract, consolidate, transform, and deliver volumes of disparate, often poorly understood and documented data …

　　for conceptually important, but often poorly specified reasons …

　　to a diverse group of users with varied levels of training and skill!

　　Even more challenging, the data warehouse is required not to perform this complex task once, but to repeatedly and reliably do so, in an ongoing, timely, robust, and extensible fashion.

　　Just as data warehouses are frequently complex and challenging, so too is the process of assessing them. The challenge is compounded by time constraints – there is normally not a lot of time to perform the assessment. Assessments, by their nature, are expected to be rapid, with six weeks a typical outer limit of patience for completion. Yet, much data – both business and technical – must be collected and evaluated to find out what is right, identify what went wrong, and determine how best to proceed. As anyone who has sifted through the artifacts of a major project can testify, review and repositioning is much more challenging than starting from scratch.

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