The first thing to do in a data warehouse project is to define why it’s being built in the first place. This should be tied to the business strategy and have very specific critical success factors established. There should be measurable (quantifiable) and immeasurable (qualifiable) business value that a data warehouse should provide. Basically this sets the direction, goals and measurements for success of the project.
The very second thing that needs to be done is define the reports that will be produced by the warehouse/mart(s). This will prove to be the litmus test for what you did in your first step and set the stage for everything else you do in the project.
After all, the sole purpose for creating a data warehouse is to enable the decision makers of an organization to make decisions based on how the company is performing. If the leaders of an organization are not getting actionable information then there’s no point in going through all this effort.
Establishing the business need is valuable, but they’re just words on the page. You need to get report mock-ups in front of whoever will end up using them when they go on-line. These mock-ups should good enough to be interpreted and evaluated visually. There will be a few reports that already exist in Excel or from a legacy system. Some will need to be created from scratch.
The process of defining these reports will have the following benefits:
- Keeps the key stakeholders of the project actively engaged in the process. They can wrap their arms around this.
- Validates most of your success factors. The results of the reports should tie directly to many of those defined in the first step.
- Identifies what will functions and features will be needed in your reporting tool – static reports, drill through, customizations, method of delivery, format, etc.
- Identifies which reports are likely to be more challenging than others and which to pay special attention to. Enables you to start mobilizing your team to tackle potential setbacks early.
- Most, if not all, of your dimensions and facts will be defined and will guide how they should be designed in the data warehouse/mart and to what level of detail (grain) they should go down to.
- Gives a good idea on how the metadata/objects in the reporting tool will need to be structured.
- Gives you leads as to where the data currently resides as a natural part of this process (bigger deal in larger organizations with many data silos).
So this process will give the direction and set the tone for the rest of the project.
Now you are well on your way to uncovering the most overlooked benefit in data warehousing.
