The Goals of a Data Warehouse.

When organizations lose the plot on their data management systems it grinds sense-making to a halt. To address the universal issues people bring up in poorly managed data environments, Kimball and Ross present a catalog of goals that a data warehouse should fulfill.

The DW/BI system must make information easily accessible. The contents of the DW/BI system must be understandable. The data must be intuitive and obvious to the business user, not merely the developer. The data’s structures and labels should mimic the business users’ thought processes and vocabulary. Business users want to separate and combine analytic data in endless combinations. The business intelligence tools and applications that access the data must be simple and easy to use. They also must return query results to the user with minimal wait times. We can summarize this requirement by simply saying simple and fast.

The DW/BI system must present information consistently. The data in the DW/BI system must be credible. Data must be carefully assembled from a variety of sources, cleansed, quality assured, and released only when it is fit for user consumption. Consistency also implies common labels and definitions for the DW/BI system’s contents are used across data sources. If two performance measures have the same name, they must mean the same thing. Conversely, if two measures don’t mean the same thing, they should be labeled differently.

The DW/BI system must adapt to change. User needs, business conditions, data, and technology are all subject to change. The DW/BI system must be designed to handle this inevitable change gracefully so that it doesn’t invalidate existing data or applications. Existing data and applications should not be changed or disrupted when the business community asks new questions or new data is added to the warehouse. Finally, if descriptive data in the DW/ BI system must be modified, you must appropriately account for the changes and make these changes transparent to the users.

The DW/BI system must present information in a timely way. As the DW/ BI system is used more intensively for operational decisions, raw data may need to be converted into actionable information within hours, minutes, or even seconds. The DW/BI team and business users need to have realistic expectations for what it means to deliver data when there is little time to clean or validate it.

The DW/BI system must be a secure bastion that protects the information assets. An organization’s informational crown jewels are stored in the data warehouse. At a minimum, the warehouse likely contains information about what you’re selling to whom at what price—potentially harmful details in the hands of the wrong people. The DW/BI system must effectively control access to the organization’s confidential information.

The DW/BI system must serve as the authoritative and trustworthy foundation for improved decision-making. The data warehouse must have the right data to support decision-making. The most important outputs from a DW/BI system are the decisions that are made based on the analytic evidence presented; these decisions deliver the business impact and value attributable to the DW/BI system. The original label that predates DW/BI is still the best description of what you are designing: a decision support system.

The business community must accept the DW/BI system to deem it successful. It doesn’t matter that you built an elegant solution using best-of-breed products and platforms. If the business community does not embrace the DW/BI environment and actively use it, you have failed the acceptance test. Unlike an operational system implementation where business users have no choice but to use the new system, DW/BI usage is sometimes optional. Business users will embrace the DW/BI system if it is the “simple and fast” source for actionable information.

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