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There are three main ways to get a high-speed Internet connection at your home. These methods are all known as broadband connections. These connection types, which you ve probably heard of, are listed here:

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If you were to try this version in the program shown earlier, the following call to CopyInsert( ) would not compile because int is a value type, not a reference type:

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You can insert or replace characters within a string by using insert( ) and replace( ). The prototypes for their most common forms are shown here: string &insert(size_type start, const string &strob); string &insert(size_type start, const string &strob, size_type insStart, size_type num); string &replace(size_type start, size_type num, const string &strob); string &replace(size_type start, size_type orgNum, const string &strob, size_type replaceStart, size_type replaceNum); The first form of insert( ) inserts strob into the invoking string at the index specified by start. The second form of the insert( ) function inserts num characters from strob, beginning at insStart, into the invoking string at the index specified by start. Beginning at start, the first form of replace( ) replaces num characters from the invoking string, with strob. The second form replaces orgNum characters, beginning at start, in the invoking string with replaceNum characters from the string specified by strob, beginning at replaceStart. In both cases, a reference to the invoking object is returned. You can remove characters from a string by using erase( ). One of its forms is shown here: string &erase(size_type start = 0, size_type num = npos); This removes num characters from the invoking string, beginning at start. A reference to the invoking string is returned. The following program demonstrates the insert( ), erase( ), and replace( ) functions:

design dimensions up front not just for the current data mart, but with an eye toward handling an entire enterprise data warehouse This is true of any dimension that can be used across multiple data marts Time, product, employee, and customer are just a few examples of dimensions that commonly are used across multiple data marts Whether these tables are actually only stored once and linked to different fact tables, or whether they are physically stored multiple times, their structure should be the same Using conformed dimensions prevent what are sometimes called stovepipe data marts, or marts that stand alone in their own silo and cannot be integrated with other data marts Slowly Changing Dimensions One of the biggest issues you ll encounter when dealing with dimensions is how to handle changes.

Answers: 1,2,5

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