How To Do a Data Warehouse Assessment (And Why)

Why Assessments and an Assessment Methodology are Needed – What an Assessment is

In the relative time scale of technology change, data warehousing has been around for a while. Discussion of “the mature data warehouse” and “second generation warehousing” is becoming increasingly common. Many, if not most, large organizations have something that they call a data warehouse, and they are likely to have some data marts tailored to the needs of specific work groups. A typical large enterprise today is most likely to be at the beginning of, or in the midst of, a data warehouse initiative. In some cases, there may be a history of several unsuccessful or partially successful data warehouse initiatives.

Regardless of actual or perceived maturity of data warehouse implementations, warehousing has yet to mature as a discipline. Data warehousing is still relatively young both in terms of proven methodologies, and in availability of experienced practitioners. In part, this is due to the inherent complexity of data warehousing. From identifying and extracting data, to providing the right access functions and information views, the data warehouse involves a wide range of processes, rapidly evolving tools, development methods, and required expertise. It's not surprising, then, that many data warehousing initiatives have failed to meet expectations, deliver business value, or realize their full potential.

Nonetheless, the pressure for delivery of effective data warehousing solutions continues to grow. Facing a multitude of business drivers -- ever increasing competition, more sophisticated and better informed consumers, changing markets, changing regulatory environments, and many more pressures – organizations are driven to respond with better targeted products, improved customer relationship management, and greater operational efficiency. Responding effectively to the pressures demands more accurate, reliable, timely, complete, insightful, and useable information and analysis.

Well-informed business processes are essential, and failure is not an option, so organizations press ahead data warehousing initiatives. Successful data warehousing organizations may well be the successful business enterprises of the future. Yet the urgency of market pressures, along with pure financial considerations, make it crucial that: 1) past errors are not repeated, and 2) whatever is correct and useable out of past data warehousing efforts be identified and leveraged.

These introductory comments describe the overall state of affairs for many companies today. Current warehousing efforts have been initiated in and environment of previous attempts and existing components. There are needs to learn quickly from experience, to find the right road, to salvage what is good and useful, and to move forward. Meeting these needs is the purpose of a data warehouse assessment. The essence of data warehousing assessment – the what, why, and how of assessment – is directed at refining the warehousing process and revitalizing the warehousing initiative. Such assessments often represent the logical starting point of a renewed data warehouse life cycle.

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.

The challenge of data warehouse assessment, then, is that there is a lot of complex