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Accommodating possible changes to dimensions complicates our loading dimensions example from the previous section For example, a Type 1 dimension requires that each dimension value encountered must rst be checked to see if it exists If it does not, then it can be inserted as described If it does exist, then a check is performed to determine whether attributes have changed (eg, whether the employee name changed), and an update is performed if required This type of conditional logic is another reason to use Integration Services to load data, as it simpli es the task and performs most operations quickly in memory A common practice for detecting changes is to create and store a checksum of the current data values in the dimension, and then calculate the checksum on each dimension row read, comparing the two checksums to determine whether a change has occurred.

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This practice minimizes the amount of data read from the database when performing comparisons, which can be substantial when a large number of attributes are involved While there is a small chance that different rows will return the same checksum, the risk/reward of this approach is frequently judged acceptable Type 2 dimensions extend the idea of Type 1 s insert-or-update regimen If a dimension row does not exist, it is still inserted, but if it exists two things need to happen First, the existing row of data is expired it continues to be used by all previously loaded fact data, but new fact data will be associated with the new dimension row Second, the new dimension row is inserted and marked as active.

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There are a number of ways to accomplish this expire/insert behavior, but a common approach adds three columns to the dimension table: effective start and end dates, plus an active ag When a row is initially inserted, the effective start is the date when the row is rst seen, the end date is set far in the future, and the active ag is on Later, when a new version of the row appears, the effective end date is set and the active ag is cleared It is certainly possible to use only the active ag or date range alone, but including both provides both easy identi cation of the current rows and change history for debugging..

4. If you plan to have your certificate signed by a CA (including one that you run yourself), generate a public key and a certificate signing request (CSR):

he network resource library provides functions for working with drives, network shares, services, open resources, and user sessions. The sections that follow show the source for the script, as well as how the script can be used.

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ith the growing availability of broadband Internet connections and a popular desire to run personal Web sites and Web logs (blogs), an increasing number of people are setting up Web application servers on their home Internet connections. Web applications are also finding more popularity in business environments because Web applications reduce the number of programs that need to be maintained on workstations. One popular variety of Web application server is what has recently come to be known as a LAMP server because it brings together Linux, Apache, MySQL, and PHP. LAMP servers combine components from several open source projects to form a fast, reliable, and economical platform for other readily available applications. This chapter helps you install and configure your own LAMP server. It begins with an introduction to the various components, guides you through the installation and configuration, and finishes with the installation of a sample Web application. The examples in this chapter are based on a system running Debian GNU/Linux but conceptually should work on other distributions, if you take into account that other Linux systems use different ways to install the software and start and stop services. Descriptions of how to set up LAMP configuration files, however, should work across multiple Linux distributions with only slight modifications. You can find more information about Debian in 9.

Fact dimensions are those derived directly from the fact table when a fact table contains both fact and dimension data. No settings are required beyond the relationship type. Only one dimension can have a fact relationship with a given measure group, effectively requiring a single fact dimension per fact table containing all dimension data in that fact table.

If you set the relationships between the tables at the table level, the query will automatically bring the links in as you add the tables. The default link type is always an inner join. However, you will still have to specify an outer join if you wish to change to that type (left or right).

Source: Chen et al.. 2003,

Figure 3-71

You supply the series of values used in the iterations in the list parameter. There are several different ways that you can specify the values in the list.

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