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Paul Volcker: What I find fascinating is that, even though the market is down, executive compensation has not come down significantly Stock options, in particular, have continued to be as high, or higher, as in the past Don Delves: In recent years, you have been very vocal about your opposition to excessive use of stock options Volcker: What I am opposed to are fixed-price stock options for large, broadly held companies When you talk about stock options, it s easier to think about it the other way around A private company that s a start-up can do what it wants It can choose to give away stock in the form of options, largely because it doesn t really have any cash I would say the same thing applies pretty much for a technological, publicly held company with a large concentrated ownership.

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This arrangement is the foundation for many highly successful data warehouse implementations. Since they are both dimensional, cubes and stars have a natural affinity. Many multidimensional products have been specifically built to support the design and creation of cubes based on an underlying star. This will be further explored later in this chapter.

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An aggregate schema is similar to a database index. Like an index, it takes up some extra space, and it makes queries go faster. Once it is defined, however, an index becomes invisible. Someone writing a query does not need to specify that it should be used, and no one needs to update the index as data changes. These things happen automatically. Aggregates do not necessarily share this invisibility. As you have seen, aggregates require attention on two fronts: It is necessary to write (or rewrite) queries to take advantage of the aggregate. It is necessary to load and maintain the aggregate, keeping it in sync with the original schema. Ideally, you shouldn t have to worry about these things. A truly invisible aggregate would automatically be exploited whenever appropriate and automatically updated as the original schema changes. Many software products strive to make this a reality. Some tools can rewrite queries automatically; some can generate and maintain aggregates; some can do parts of both. Software features that help achieve this invisibility may be found in reporting tools, ETL tools, and database management systems. Implementations vary widely, and none are perfect. Some basic principles will help you understand how to evaluate and leverage the capabilities of available tools. The two aspects of invisibility are aggregate navigation and aggregate generation. For some tools, these are separate concepts; for others, they are closely linked together.

A type 3 change is not a one-time-only process. It can be repeated once, twice, or as many times as needed. Robert Davis s region, for example, may subsequently be changed again. Perhaps as a result of redrawing the region boundaries, he is redesignated as being in the Southeast. When this occurs, what was formerly in region_current (Northeast) is moved to region_previous. The new value (Southeast) is placed in region_current. A type 3 change preserves only one old version of the changed attribute. Once a second change occurs, the fact that Robert Davis was once in the East region is lost. In some cases, it may be useful to maintain multiple values. This can be done by designating three, four, or however many versions of the region column are required. Each time a change occurs, the values are all shifted among these columns. With multiple versions, the columns can be difficult to name. If the changes occur on a predictable basis, they might be named region_2009, region_2008, region_2007, and so forth. This approach has two distinct disadvantages. First, it requires the DBA to periodically change the names of columns. For example, if requirements call for the current version and the two previous versions, it is necessary at the end of 2009 year to drop the 2007 column and add one for 2010. Second, encoding the year into the column names means new queries and reports will need to be designed each year to refer to the new column names. An alternative that avoids these drawbacks is to name the columns region_current, region_last_year, and region_two_years_ago.

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