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The idea of buy low, sell high is as old as trading ownership of properties. It is the basis of all business. Buy a property at one price and sell it at a higher price. The difference between the buy and sell transactions is profit. To make a profit is the reason to buy and sell stock. It is the one axiom almost everyone understands but many have trouble doing. An investor hears that Company ABC is buying out XYC Company. The stock had been trading at $24.50 a share, but the buyout is

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When data is to be cleansed, it is necessary to have a set of rules that describe what must occur. In some cases, it is possible to define simple data-driven requirements in tabular format. These may be instantiated as physical tables, allowing the rules to be maintained separately from ETL code. However, this separation may also hamper processing efficiency. Frequently, the ETL process will encounter a fact for which it cannot identify valid dimensional detail. Failure to load this data may result in inconsistencies between the star schema and the operational systems. Special techniques can be employed that allow it to be loaded in the absence of critical dimensional detail, so that the two systems are reconciled. This will require taking measures that allow the facts to be adjusted once the required detail is available.

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Now you know the story. But it doesn t end there. It s time to add a new chapter to the accounting story. To get that started, I spoke with Jim Leisenring, board member of the International Accounting Standards Board (IASB). Leisenring may be the most outspoken advocate of stock option expensing and has been for more than 10 years. In his mind, not only does stock option expensing make sense, it is imperative for sound accounting practices and fair executive compensation. In the early 1990s when the Financial Accounting Standards Board (FASB) tried to adopt expensing, Leisenring (then a member of the FASB) was among those who testified in favor of the plan before Congress. Although the FASB failed at that time, in the face of mounting opposition from corporations, accounting firms, Congress, and the Securities and Exchange Commission (SEC), Leisenring sees a different climate today. Leisenring predicts that the FASB will adopt an option expensing rule, in part due to the support of the IASB.

Data can be changed, or cleaned up, in a variety of ways Some kinds of cleansing are best done as part of the process that loads the data warehouse, while some are not It is reasonable, for example, to standardize the formatting of phone numbers while loading a star schema On the other hand, it is definitely not a good idea to reassign an order transaction from one salesperson to another These are black and white extremes, but in between lies a gray area What should one do, for example, if a salesperson was entered inconsistently How does one sort out the kind of cleansing that is reasonable from that which is not The answer lies in the fundamentals of data warehousing The purpose of a data warehouse system is to provide operational data that has been restructured for analysis.

expected to be at $2800 The investor knows there is some risk involved and so decides to think about buying 100 shares The following afternoon the investor calls the broker and learns that XYZ Company is now trading at $3000 A feeling of panic overcomes the investor because the price is above the buyout price already Better place that buy order An order to buy 100 shares of XYZ Company is placed and filled at $2750 a share The following week the investor calls the broker to check on XYZ Company and learns that it is now trading at $2550 That s a $2 loss per share Even more frightening, it s a 10 percent loss Trying to restrain the feeling of panic, the investor gives instructions to sell the 100 shares of XYZ Company at the market The order is entered and executed at $25.

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