Creating Aggregation Tables with the Summarized Aggregation Table Wizard

To create an aggregation table (that is, the target table) with the Summarized Aggregation Table wizard, respond to the wizard's prompts.

How to Enter General Information about the Aggregation Table

To specify general information about the aggregation table, perform the following steps:
  1. Enter the name of the table in the Name field. This field can contain up to 60 characters. It must be unique within the metadata folder. It must also be unique among all other table names within the application server. A value is required in this field.
    Note: The name of this aggregation table will be displayed on subsequent pages of the wizard.
  2. (Optional) Enter the identifying information in the Description field. This field can contain up to 200 characters.
  3. (Optional) In the SAS table name field, you can accept the default value, or enter the physical name of the aggregation table.
  4. (Optional) In the IT data mart field, you can accept the default value, or enter the name of the IT data mart. The IT data mart field contains the job in which the Aggregation transformation is located.
  5. (Optional) In the Location field, you can accept the default value, or enter the metadata path to the metadata folder where the job that contains the Aggregation transformation is stored.

How to Specify Library Information

If this aggregation table is the first target table that is specified for this Aggregation transformation, an additional page of the wizard opens. This page prompts you for the physical target location and for information about the SAS library where the data will be stored. When this page opens, the following fields are already specified with default values. If you want to modify these fields, perform the following steps:
  1. In the Name field, enter the name of the library that contains all aggregation tables that are associated with the Aggregation transformation that you are working with. This field can contain up to 60 characters. A value is required in this field.
  2. In the Description field, enter the information that describes the library. It can contain no more than 200 characters. It is an optional field.
  3. In the Server field, enter the application server that you specified for the IT data mart that you are working with. The default application server is the SASITRM server. A value is required in this field.
  4. In the Libref field, enter the name that is temporarily associated with the library. The libref or an aggregation library is a concatenation of AGG and a random number (for example, AGG27040). A value is required in this field. The libref name must be unique within the application server.
    Note: The following naming rules apply to the libref:
    • The libref can consist of no more than eight characters.
    • The libref must begin with a letter (A through Z) or an underscore (_).
    • The remaining characters of the libref must be letters (A through Z), numerals (0 through 9), or an underscore (_). The libref cannot contain spaces.
  5. In the Path specification field, enter the location where the tables for this library are to be stored. You must specify a location for the tables that is within the IT data mart that is specified in the IT Data Mart field.
    Enter this field manually or click Browse to select a location from the Select a Directory dialog box that displays the directory structure on the server's file system. A value is required in this field.

How to Select a Filter

Filters can limit the amount of data that is input to an aggregation table. To select a filter and a column for data-duplication checking, perform the following steps:
  1. From the drop-down list in the Select filter field, select the filter that you want to use. The selected filter is displayed in the Select filter field and its corresponding expression is displayed in the Expression field.
  2. The Expression field displays the formula that defines the filter. It cannot be changed from this location. For information about how to modify the expression field of a filter, see Modify a Filter of an Aggregation Transformation.
  3. Check the Enable data duplication checking box to indicate that you want data-duplication checking to be performed as the data from the source table is read. If checked, this option removes duplicate data items from the resulting target table.
    Note: This option is enabled only if LSTPDATE is found in the source table. (The default value for this option is deselected.)
If you want to create a new filter to use for your aggregation table, perform the following steps:
  1. Click the Add New button to open the Add Filter dialog box.
  2. In the Name field, enter the name of the new filter. The name field can contain no more than 60 characters.
  3. In the Expression field, enter the formula.
  4. Click OK.
Note: For more information about how to work with filters, see Working with Aggregation Transformation Filters .

Specify Aging

Managing Your Data: Aging and Purging Options

SAS IT Resource Management provides several ways of managing the amount of data that is kept in the aggregation tables of your IT data mart. You can apply the aging and purging functions to both simple and summarized aggregations. The selection of the aging and purging attributes for a simple or a summarized aggregation table can be performed on the Specify aging page of the wizard.
  • Purge Aggregated Data
    Purging the data removes the data from the target table before the new data is loaded.
  • Age Aggregated Data
    You can specify whether and how you want to age your data when you create the Aggregation transformation. Based on these specifications, data will be kept in the aggregation tables or aged out of them.
    By entering a value for the Age limit in days, you are specifying the age range that data will be present in the table. The minimum number of days is 1; the maximum number of days is 9999.
    Note: Columns that are used for aging are DATETIME columns. For these columns, one day of aging extends over 24 hours of data collection, which might extend over one or more days.
    You are not specifying that the data is to be aged out after that number of days. Instead, the value that you specify is the number of days of data that you want to keep. Calculate what is aged out by subtracting the value of the Age limit in days from the latest date of the new or existing data. The resulting date is the date before which data will age out. For example, in the following figure, Day 9 is the latest date of the data and the Age limit in days is seven.
    Example of How Data Is Aged out
    Age Limit Example
    All data from Day 2 and earlier is aged out. All data from Day 3 through Day 9 is kept. However, because no data was loaded on Day 4 and Day 8, only five days of data is kept, namely the data for Day 3, Day 5, Day 6, Day 7, and Day 9.
Note: If you reduce the aging value, the change takes effect the next time the job is run, even if there is no new data.

How to Specify Purging Criteria

To purge the target table before you load new data, check the corresponding check box. This action removes the data that was processed in previous executions of the job.

How to Specify Aging Criteria

You can specify whether and how you want to age your data when you define the aggregation target table. Based on these specifications, data will be kept in the aggregation table or aged out of it. To specify aging criteria for the target table, perform the following steps:
  1. To perform aging for the target table, check the corresponding check box. This action enables you to select the column to be used for aging and to specify the format of that column.
    • The Column field displays a list of the columns from the source table that are available to use for aging the data. From the drop-down list, select the column that you want to use. It is displayed in the Column field. The format of the selected field is displayed.
      Note: If you want to specify percent change for a variable, you must select an aging column. SAS IT Resource Management uses that aging column in order to calculate the period-to-period changes for that variable. The selected aging column is automatically added to the list of class columns for this aggregation table.
    • The Date or Datetime option is automatically selected, based on the contents of the column that you selected for aging. Changing this option is permissible, but it is not recommended.
      Note: Specify the option that reflects the type of column that you chose. For DATE values, the aging counts by days. For DATETIME values, the aging counts by the number of seconds in a day.
  2. Use the spinner to select the number of days age limit.
  3. To specify the completed day, check the corresponding check box. This action enables you to select the column to use to determine whether a day is complete. (This option is enabled if aging has been specified for this aggregation table and the source table has a column called DATETIME.)
    This feature is useful only for tables where the aging column represents a DAY or less. For example, this feature is not useful for WEEKDATE aggregations.
    Note: If the Apply completed day option is deselected on an existing aggregation table that previously selected that option, the rank columns of that table are analyzed. If they depend on Completed Day being selected, a message is displayed that lists the rank columns that would be affected and the deselection of the Completed Day option is not permitted.
  4. Use the Cut off time field to specify when a day is completed. Use the spinners to specify the hours, minutes, and whether the time is a.m. or p.m.

How to Specify Class and ID Variables

On the Specify class and ID variables page, you can specify the columns from the source table that are to be included in the target aggregation table as class variables and as ID variables. After the class and ID variables have been selected, you can modify the name, label, and the format attributes of the output columns. These changes can be performed on the Specify column details page of the wizard for summarized aggregations.
  • A class variable is used to group or classify data. For example, the value of a class variable could be a device address.
    At least one variable must be selected as a class variable.
    Note: If aging is being performed on this target aggregation table, then the aging column is automatically added to the list of class columns. The aging column cannot be deleted from the list of class variables if it is in use as the aging column. If aging is turned off, the column can be removed from the list of class variables.
  • An identification (ID) variable contains an alternate identifier for the data in a class variable. For example, the value of the corresponding ID variable could be the name of a particular device.
    ID variables are not required.
To select class columns for the target aggregation, perform the following steps:
  1. Highlight the columns in the Available variables panel that you want to select as class columns.
  2. Click the right arrow to move those columns into the Selected class variables.
To select ID columns for the target table, perform the following steps:
  1. Highlight the columns in the Available variables panel that you want to select as ID columns.
  2. Click the right arrow to move those columns into the Selected ID variables.
Note: If a variable is based on a time period that is greater than your aging column, do not specify it as a class column. Instead, specify it as an ID column. For example, if your aging column is DAYDATE, do not specify WEEKDATE as another class column. Instead specify it as an ID column.
You can select the entire list of available columns by clicking the double right arrow. Back arrows can be used to deselect one, several, or all columns.
After your data has been aggregated, you can change the class list. If you remove columns from the class list, the existing data in the summarized aggregation table is merged again so that it matches the new class list. If you add new columns to the class list, then these new columns in the summarized aggregation table will have a missing value (for numeric) or blank value (for character) in the existing data. (You cannot remove a class or ID column if it is used as the source for a join column in another aggregation table. Similarly, you cannot remove a class or ID column if it is used as the source column of a rank column in this aggregation table.)
The value that is assigned to the ID variable is the last value that is read into the group that is defined by the unique combination of class variables.
Note: If an input column is given a role as a class variable, ID variable, or a statistic, it cannot simultaneously be assigned a different role. Therefore, it will not be available for selection. If all available variables are assigned as class or ID variables, then no variables will be available to be used as analysis variables. In that case, the Select analysis variables page will not be displayed. Similarly, if no analysis variables are selected, the Specify statistics page will not be displayed.

How to Specify Column Details

On the Specify column details page, you can modify the Target Column Name, Target Column Label, and Target Column Format for any of the input columns that you are including in the target aggregation table.
The Target Column Name can be any legal SAS column name. It must be unique within its table.
To modify the Target Column Format, double-click in the field and select the new format from the drop-down list.

How to Specify Analysis Variables

On the Select analysis variables page, you can select analysis variables that can be used to calculate statistics. If no analysis variables are selected, no statistics can be specified for this aggregation and the Specify statistics page of the wizard is not displayed.
Note: If you do not want to specify statistics, ranking, percent change, join columns, or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

Specify Statistics

About Specifying Statistics

On the Specify statistics page, you can calculate or delete one or more statistics on analysis variables that you selected on the previous page. These variables are displayed in a grid format, which contains a row for each analysis variable. The grid contains the following columns: Statistics, Weight By, Target Column Name, Target Column Description, and Target Column Format. Except for the Statistics column, which displays the names of the selected analysis variables, the columns of the grid are blank until the statistic is specified.
Note: For the list of statistics that SAS IT Resource Management enables you to create, see Statistics.
Note: If you do not want to specify statistics, percent change columns, rank columns, join columns, or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation target table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

How to Create Statistics for an Analysis Variable

To create statistics for an analysis variable, perform the following steps:
  1. Click New, which opens the Add Statistics window.
  2. In the Select analysis variables panel, check the box next to the analysis variable for which you want to specify statistics. (Checking multiple analysis variables enables you to specify the same statistics for all the analysis variables that you selected. Otherwise, check an analysis variable and specify the statistics for it individually.)
  3. To specify unweighted statistics, in the Statistic Types panel, check the statistics that you want to create. The counter that is next to All Selected Statistics displays the number of statistics that you selected.
  4. To specify weighted statistics, in the Weighted Statistic Types panel, select the variable that you want to use from the Weighted by drop-down list. Then check the weighted statistics that you want to create.
  5. In the following display, Count, Geometric Mean, Weighted Geometric Mean, and Weighted Mean statistics for the DATETIMEONEMIN analysis variable are to be created.
    Add Statistics Window
    Add Statistics Window
  6. Click OK to add the requested and any underlying statistics to the grid under the analysis variable. The row displays these statistics along with its attributes, such as Weight By, Target Column Name, Target Column Description, and Target Column Format. These fields contain the default values that are associated with the statistics. To modify a field on this grid, highlight it, and change it as needed by typing the revision in the field.
  7. The following display shows the newly added Count, Geometric Mean, Weighted Geometric Mean, and Weighted Mean statistics that will be generated for the DATETIMEONEMIN analysis variable.
    Specify Statistics Window with Newly Added Statistics
    Specify Statistics Window with Newly Added Statistics

How to Delete a Statistic

To delete a statistic from the list of statistics that will be created for an analysis variable, perform the following steps:
  1. Select the statistic.
  2. Click Delete. If the statistic that you want to delete is used to generate another statistical column, a warning message is displayed that lists the statistical columns where the statistic is needed. You must first delete those statistical columns before you can delete this statistic. (You cannot remove a statistic column if it is used for a rank column, percent change column, or join column.)
Note: Deleting a statistic that depends on another statistic does not delete any underlying statistic.
Note: If you do not want to specify percent change, ranking, join columns, or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

Deleting Multiple Statistic, Percent Change, Rank, and Join Columns

In some instances, you might want to delete multiple columns at the same time. For example, you might want to delete all of the statistics for a particular analysis variable, or only some of the statistics. You can delete all of the statistics for a particular analysis variable by either selecting all the statistics individually, or by selecting the analysis variable itself. Either action will accomplish the same purpose.
However, if your selection of columns to delete includes an analysis variable and some, but not all, of the statistics for that analysis variable, a message is displayed. The message states that you selected conflicting choices and, therefore, no columns will be deleted. The message advises you to select either an analysis variable or one or more statistics.
A similar scenario can be seen in other variable selection screens, such as for percent change, rank, and join columns. In each case, you can select either the root input column or the individual output columns for deletion, but selecting a mixture of the two might be a conflict.

Specify Percent Change

About Specifying Percent Change

Percent change information is displayed in a grid format, which contains a row for each statistic that is being calculated. The grid contains the following columns: Statistics, Weight By, Statistic Column Name, Target Column Name, Target Column Description, and Target Column Format. Except for the statistic that is being calculated, all cells of the grid are initially blank.
On the Specify percent change page, you can specify the percent change for statistics. If you want to specify percent change for a variable, you must have selected an aging column. SAS IT Resource Management uses that aging column in order to calculate the period-to-period changes for that variable.
Note: If you do not want to specify percent change columns, rank columns, join columns, or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation target table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

How to Specify Percent Change Calculation for a Statistic

To calculate the percent change for a statistic, perform the following steps:
  1. Click New, which opens the Add Percent Change Columns window.
  2. From the list in the Available statistics column, select the statistics for which you want to calculate the percentage of change. Use the arrow to transfer those statistics to the Selected statistics column.
  3. Click OK. The selected statistics are added to the Percent Change grid, and you are returned to the Percent Change page.

How to Remove Percent Change Calculation for a Statistic

To remove the calculation of percent change for a statistic, perform the following steps:
  1. Select the statistic.
  2. Click Delete.
Note: If the percent change column is used for a rank column in this table or a join column in another table, a dialog box is opened that displays where the column is used. You must remove those columns before you can delete the percent change column.
For information about deleting multiple percent change columns, see the information in the preceding topic called "Deleting Multiple Statistic, Percent Change, Rank, and Join Columns.”

Specify Ranking

About Ranking

The ranking of data determines the position of the value of a variable or a value within a selected group of class variables. You can specify that ranks be computed on class variables, ID variables, or statistical variables. Only numeric variables can be ranked.
SAS IT Resource Management computes a dense rank, which means that the rank numbers are sequentially numbered, without gaps. The ranks start with 1 and are incremented by 1. Ties receive the same rank. For more information about ranking, see “The RANK Procedure” chapter in the Base SAS Procedures Guide.
Ranks are computed before the calculation of computed columns so that ranks can be used in the calculation of a computed column.
On the Specify ranking page, you can specify the variables that you want to rank and how these variables should be ranked. You can also delete a rank variable. Rank variables are displayed in a grid format, which contains a row for each defined rank variable. The grid contains the following columns: Rank Columns, Target Column Name, Target Column Description, Rank Order, Rank Grouping, and Completed Days, which are all initially blank until you add a ranking specification for a variable.
Note: Jobs that calculate rank variables might require lengthy processing time because the data might have to be read multiple times. For best results, minimize the number of rank variables that you specify.
Note: If you do not want to specify rank columns, join columns, or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation target table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

How to Specify Ranking for a Variable

To specify ranking for a variable, perform the following steps:
  1. Click New to open the Add Rank window.
  2. To rank variables over all the data, click the corresponding option. (The list of variables with this option includes numeric class and ID columns that you selected from the source table as well as the statistics columns that you specified on the previous page.)
    Then, in the Select variables to rank column, check the variables that you want to rank.
  3. Alternatively, to rank variables over specific class variables, click the corresponding option. (The list of variables with this option includes only the statistics columns that you specified on the previous page.) In the Rank over the following class variables box, check the class variables over which you want to rank selected variables.
    Then, in the Select variables to rank column, check the variables that you want to rank.
    Note: You can select any class variables over which to rank the selected statistic. However, you should leave at least one class variable deselected. The class variables that are not selected are the variables over which the statistic is to be ranked. For example, you might have an aggregation table of average CPU Utilization, and the class variables are DAYDATE, DOMAIN, and MACHINE. If you request a descending rank of Average CPU Utilization using a Rank Grouping of DAYDATE and DOMAIN, then that request would result in a ranking of Average CPU utilization for all machines within the DOMAIN for the given DAYDATE. Thus, the observation where the rank value is 1 would be the machine with the highest average CPU utilization, ranked separately for each unique DOMAIN and DAYDATE combination. Alternatively, if you request a descending rank of Average CPU Utilization using a Rank Grouping of DAYDATE, DOMAIN, and MACHINE, then that request would result in a ranking of Average CPU utilization for a single row of data, which is not a useful ranking.
  4. In the Rank Order box, click Ascending or Descending.
    Note: In a descending rank, the largest value gets a rank of 1, with the next largest value getting a rank of 2, and so on. In an ascending rank, the smallest value gets a rank of 1, and the next smallest value gets a rank of 2, and so on.
  5. To rank only completed days, check the corresponding box.
    Note: This option is available only if the Apply completed days option was selected on the Specify aging page of this wizard. Furthermore, if a rank is defined to have completed days, then you cannot disable the Apply completed days option, and you cannot disable aging.
  6. Click OK to add the rank to the list of rank columns.

How to Delete a Rank Variable

To delete a rank variable, perform the following steps:
  1. Select the variable that you want to delete.
  2. Click Delete.
    You cannot delete a rank column if it is used as the source for a join column in another aggregation table. You must first delete the join column from the other table before deleting the rank column.
For information about deleting multiple percent change columns, see the information in the preceding topic called "Deleting Multiple Statistic, Percent Change, Rank, and Join Columns.”
CAUTION:
Rank columns are often used as filters in information maps. If you remove a rank column that is used as a filter in an information map, then the information map, the information map job, and the report jobs that depend on that filter might fail to run.
To avoid processing errors, delete any reference to a deleted rank column in any information map, report, or transformation that uses that column.
Note: If you do not want to specify join columns or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation target table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

Specify Join Columns

About Specifying Join Columns

The following rules govern the join function:
  • Simple aggregations cannot serve as the source of a join column.
  • Only ID, statistic, percent change, and rank columns can be joined from a summarized aggregation.
  • A simple aggregation (the destination) can join columns from a summarized aggregation (the source) if and only if every class column in the source table exists as a column in the destination table.
  • A summarized aggregation can join columns from another summarized aggregation if and only if the complete class list of the source table is a proper subset of the union of class and ID list of the destination table.
Note: Jobs that include joined columns might require lengthy processing time. For best results, minimize the number of joined columns that you specify.
Information about join columns is displayed in a grid format, which contains a row for each column that is to be joined. The grid contains the following columns: Source Columns, Target Column Name, Target Column Description, and Target Column Format. The entries in the grid are initially blank.
On the Specify join columns page, you can specify columns from other aggregation tables in this Aggregation transformation to join with columns in this target table.
CAUTION:
If you changed the list of class columns for an aggregation table by adding an aging column, you might have made the join invalid.
This case would break the fourth rule of the rules that govern a join.
Note: If you do not want to specify join columns or a computed column for this aggregation table, click Finish, which updates the Aggregation transformation with this new aggregation target table and returns you to the process flow diagram. For information, see Completing the Specification of the Summarized Aggregation Table.

How to Specify Join Columns

To add a join column to the table, perform the following steps:
  1. Click New. The Add Join Columns dialog box appears.
  2. Select columns from the list in the Available Columns. Use the arrow to transfer those columns to the Selected Columns panel and click OK. The selected columns are entered automatically into the appropriate cells of the grid, along with their corresponding default values for Target Column Name, Target Column Description, and Target Column Format.

How to Remove Join Columns

To delete join columns, perform the following steps:
  1. Highlight the join column in the grid of columns to be joined.
  2. Click Delete.
For information about deleting multiple percent change columns, see the information in the preceding topic called "Deleting Multiple Statistic, Percent Change, Rank, and Join Columns.”

Specify Computed Columns

About Computed Columns

A computed column stores the results of computational tasks. For example, a computed column can be used to convert unit measurements so that all the data uses the same standardized units of measurement. You can add, modify, or delete computed columns on the Add or modify computed columns page that is available in the Summarized Aggregation wizard or the Simple Aggregation wizard. By default, a computed column is numeric.
Note: If you change a computed column, the values for the computed column are recalculated for that column in all rows of the data when the job is executed. (This recalculation is performed even if no new data is added to the aggregation table.)
The Specify computed columns page displays a grid that shows the following fields for each computed column: Name, Expression, Description, Length, Type, Informat, and Format.
Tip
A computed column called TimePeriod is automatically added to every simple and summarized aggregation table. Its value is always the same as the aging column, and you can refer to TimePeriod instead of referring to the aging column directly. This technique simplifies reporting, especially in those instances where you do not know the name of the aging column. (If no aging is specified for the target table, then the field is set to missing.) The expression for this column is defined when the aggregation wizard is completed. For example, if the aging column of an aggregation table is DAYDATE, the expression for the TimePeriod computed column is DAYDATE and its expression is TIMEPERIOD=DAYDATE;
On the Specify computed columns page, you can create, modify, or delete computed columns.

How to Add a Computed Column

To add a computed column to the aggregation table, on the Computed Columns page of the aggregation wizard, perform the following steps:
  1. Click New. A new line is displayed on the grid that contains default values for the following attributes: name, length, type, informat, and format. (The default value for the name of the column is “Untitledn”, where n is the nth computed column for this aggregation.)
    Specify Computed Columns
    Specify Computed Columns
  2. Enter the values that you want to use for the Name, Expression, and Description fields. You can enter values for the Length, Type, Informat, and Format fields, or you can accept the default values for these fields.

How to Modify a Computed Column

To modify a computed column, perform the following steps:
  1. Select the column from the drop-down list. You can change the values of this column as needed.
  2. In the Name field, you can change the name of your computed column. The name of the computed column can be any legal SAS name. It must be unique within the target table.
  3. In the Expression field, you can specify a modified computation for this computed column by entering it in this field or by using the Expression Builder function that is provided by SAS Data Integration SAS IT Resource Management. Double-click in the field and click ... to open the Expression Builder window.
    Expression Builder Dialog Box with IT Formulas Tab
    Expression Builder Dialog Box with IT Formulas Tab
    Apart from the many functions that are available from the Functions and Data Sources tabs of this window, the Expression Builder window provides another tab to assist you in defining the computation for this column—the IT Formulas tab.
    • The Functions tab of the Expression Builder window lists a variety of functions, conversions, and other actions that you can specify in your expression. Select the function that you want to use in the expression and click Insert.
    • The Data Sources tab of the Expression Builder window lists all the columns that are generated in the aggregation table output. Select the column that you want to use in the expression and click Insert.
      For simple aggregations, the Data Source tab displays all the output columns that you selected for the simple aggregation table. For the summarized aggregation table, the Data Source tab displays all the class, ID, statistic, percent change, rank, and join columns that you selected for the summarized aggregation table. In addition, it displays the system-generated LastUpdated, CompletedDay, and ContribCount variables.
      All variable names that are used in the computation are the output column names. For example, if you choose to use an input column named SYSTEM as a class variable, you might rename it MACHINE. Then, if you want to use that column when defining a computed column, you should refer to that column as MACHINE, not SYSTEM.
    • The IT Formulas tab lists the formulas that you have defined as well as the formulas that are supplied with SAS IT Resource Management. Select the formula that you want to use and click Insert.
    In addition to the conventional rValue expression (where the expression consists of code that is appropriate only for the right-hand side of an assignment statement), SAS IT Resource Management also supports more complex expressions. For example, your expression can use SAS code that might include loops, IF statements, and so on. This code must be written in valid SAS DATA step syntax.
    When you are satisfied with the expression that you defined, click OK in the Expression Builder window to close that window and place the expression in the appropriate field of the computed column.
    Note: If invoked from the Filters tab of an Aggregation transformation, the Expression Builder window does not contain the IT Formulas tab. This tab is available only when the window is invoked from the Add or modify a computed column page of the wizards for summarized and simple aggregations.
    For more information about the Expression Builder window, click the F1 key or Help from within that window.
  4. In the Description field, you can change the descriptive information about the computed column.
  5. In the Type field, you can change the type of the computed column. Double-click in the field and use the arrow to display the drop-down list of valid types (either character or numeric) from which you can select the type for this computed column. Fields that are the result of a calculation should be specified as numeric. By default, the computed column is numeric.
  6. In the Length field, you can change the length of the computed column. For numeric type columns (not character type columns), this numeric value must be from 2 through 8. (Reducing the length of a numeric computed column might introduce precision errors.) For character computed columns, the length can be from 1 through 32767.
  7. The Informat field is not used by the Aggregation transformation.
  8. In the Format field, you can change the SAS format of the computed column. Double-click in the field and from the drop-down list of valid formats, select the format for this computed column.
    You can also enter a format name if it will be available when you execute the job or when you view the data in SAS.

How to Delete a Computed Column

Deleting a computed column removes it from the metadata for a table. The column will no longer be generated when the Aggregation transformation job is run. However, deleting a computed column does not remove the column from the physical tables of aggregated data that have already been generated.
To delete a computed column from an aggregation table, perform the following steps:
  1. Select the computed column that you want to delete.
  2. Click Delete.
When you have finished working with your computed columns, click Next to continue to the final page of the wizard.
Note: After the job is redeployed and executed, changes to the computed columns will be reflected in the physical table. For information about redeploying jobs, see Redeploy All Jobs on the Server.
For information about deleting multiple percent change columns, see the information in the preceding topic called "Deleting Multiple Statistic, Percent Change, Rank, and Join Columns.”

Completing the Specification of the Summarized Aggregation Table

The final page of the wizard displays the details for the summarized aggregation table that you specified. If you are satisfied with your choices, click Finish. Click OK to return to the process flow diagram.
Aggregation tables are stored in sorted order, with an asserted SORTEDBY= data set option. The SORTEDBY assertion reflects that the data is stored in the following order:
  1. aging column
  2. alphabetical list of the remaining class columns
BY-processing can be performed using the class list, if the BY list matches the same SORTEDBY assertion. With SAS IT Resource Management, you can leverage SAS Data Integration Studio to define additional indexes for use where BY-processing is required. If you require a sorted aggregation table, you can input that table to a SORT transformation and store the resulting table wherever you want.
For information about indexes, see Indexing an Aggregation Table.
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