Data Warehouse Dining ExperienceManaging a data warehouse is similar to running a restaurant.by Margy Ross & Ralph Kimball Continued from Page 1 The Dining RoomLet's turn our attention to the restaurant's dining room. What are the key factors that differentiate restaurants? According to the popular Zagat Surveys, restaurants around the world are rated on four distinct qualities:
Most Zagat Survey readers focus initially on the food score when they're evaluating dining options. First and foremost, does the restaurant serve good food? That's the restaurant's primary deliverable. However, the decor, service, and cost factors also affect the patrons' overall dining experience and are considerations when evaluating whether to eat at a restaurant or not. Of course, the primary deliverable from the data warehouse kitchen is the data in the presentation area. What data is available? Like the restaurant, the data warehouse provides "menus" to describe what's available via metadata, published reports, and parameterized analytic applications. Is the data of high quality? Data warehouse patrons expect consistency and quality. The presentation area's data must be properly prepared and safe to consume. In terms of decor, the presentation area should be organized for the comfort of its patrons. It must be designed based on the preferences expressed by the data warehouse diners, not the staging staff. Service is also critical in the data warehouse. Data must be delivered, as ordered, promptly in a form that is appealing to the business user or reporting/delivery application developer. Finally, cost is a factor for the data warehouse. The data warehouse kitchen staff may be dreaming up elaborate, albeit expensive meals, but if there's no market at that price point, the restaurant won't survive. If restaurant diners are pleased with their dining experience, then everything is rosy for the restaurant manager. The dining room is always busy; there's even a waiting list on some nights. The restaurant manager's performance metrics are all promising: high numbers of diners, table turnovers, and nightly revenue and profit, while staff turnover is low. Things look so good that the restaurant's owner is considering an expansion site to handle the traffic. On the other hand, if the restaurant's diners aren't happy, then things go south in a hurry. With a limited number of patrons, the restaurant isn't making enough money to cover its expenses (and the staff isn't making any tips). In a relatively short time period, the restaurant shuts down. Restaurant managers often proactively check on their diners' satisfaction with the food and dining experience. If a patron is unhappy, they take immediate action to rectify the situation. Similarly, data warehouse managers should proactively monitor data warehouse satisfaction. You can't afford to wait to hear complaints. Often, people will abandon a restaurant without even voicing their concerns. Over time, you'll notice that diner counts have dropped, but may not even know why. Inevitably, the prior patrons of the data warehouse will locate another "restaurant" that better suits their needs and preferences, wasting the millions of dollars invested to design, build, and staff the data warehouse. Of course, you can prevent this not-so-happy ending by being an excellent, proactive restaurant manager. Make sure the kitchen is properly organized and utilized to deliver as needed on the presentation area's food, decor, service, and cost. We've been using this analogy for years; it strikes a cord and evolves as we discover more parallels between the restaurant and the data warehouse. The sign of a good metaphor is one that can be expanded and still hold together. Let us know if you have further embellishments to this analogy. We'll pass them along in an upcoming Kimball University Design Tip. Margy Ross [margy@ralphkimball.com] is president of the Kimball Group and an instructor with Kimball University. She cowrote The Data Warehouse Lifecycle Toolkit (Wiley, 1998) and The Data Warehouse Toolkit, 2nd Edition (Wiley, 2002). Ralph Kimball founder of the Kimball Group, teaches dimensional data warehouse design through Kimball University and critically reviews large data warehouse projects. You can reach him through his Web site, www.ralphkimball.com.
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