Topics
This chapter includes the following sections:
This section describes saving objects as inline or named. It contains the following topics:
Topics
As you work with certain objects, you can create other objects that are saved with those objects.
When you save one object with another, that object is saved "inline." You can save filters, groups, and calculated items inline. For example, you can create a group as part of an analysis. When you save the analysis, the group is saved "inline" or along with the analysis.
In addition to saving these objects inline, you can save them as individual objects with the subject area in the Oracle BI Presentation Catalog. When you save an object on its own, its becomes a "named" object. Named objects provide reusability, because you can create one object and use it multiple times with any analysis, dashboard (for filters), or dashboard page (for filters) that contains the columns that are specified in the named object. When the named object is updated and saved, those updates are immediately applied to all objects where the named object is used.
For example, after you save a group inline with an analysis, you can save the group as its own object in the catalog. You can then apply that named group from the Catalog pane to other analyses.
Named filters, groups, and calculated items are generally saved to their related subject area folder.
By saving the objects to a subject area folder, you ensure that they are available when you create an analysis for the same subject area.
Named objects saved in the /My Folders folder are available only to you. Objects saved in the /Shared Folders folder are available to other users who have permission to access the folders. If a subject area folder does not exist in your /My Folders folder or within the /Shared Folders folder, then the subject area folder is created automatically. When you save the object, the Save As dialog displays a default save path to /My Folders/Subject Area Contents/<subject area>. However, the dialog's Folders area continues to display all instances of the subject area folder in the catalog.
You can save a filter as an inline filter or a named filter.
When you create an inline filter in the Criteria Tab's Filters pane of the Analysis editor, you can optionally save the inline filter as a named filter. Named filters can also be created at the analysis level or as a standalone object from the global header.
A named filter can filter all or some of the analyses that are embedded in a dashboard or analyses that are embedded on the same dashboard page.
Saving groups and calculated items allows those functions to be re-used throughout the application.
You can save groups and calculated item as an inline or named object:
When you create a group or calculated item while editing and saving a view or while working in the Compound Layout, the group or calculated item is saved inline with the analysis.
When you work in the Selection Steps pane:
You can save a group or calculated item that is within a step as a named object in the catalog.
You can save a set of steps or the resulting members list for a column as a named object. You cannot save a set of steps as a group if one of the steps includes a calculated item.
See Adding a Group to Another Analysis.
To save a calculated item or group as a named object to the catalog:
Display the Selection Steps pane.
Click the link for the calculated item or group, then click Save Calculated Item As or Save Group As to display the Save As dialog.
Complete the dialog to save the object to the catalog.
To save a set of steps as a group to the catalog:
Display the Selection Steps pane.
Click the Save Selection Steps button to the far right of the column name.
Complete the Save Selection Steps dialog to save the group as an object to the catalog.
You use both filters and selection steps to limit the results that are displayed when an analysis is run, so that the results answer a particular question.
You use both filters and selection steps to limit the results that are displayed when an analysis is run. This means that the results answer a particular question. Together with the columns that you select for an analysis, filters and selection steps determine what the results contain. Based on the filters and selection steps, only those results that match the criteria are shown. For example, depending on the industry in which you work, you can use filters and selection steps to learn who are the top ten performers You can also learn the dollar sales for a particular brand, and which are the most profitable customers.
Filters and selection steps are applied on a column-level basis and provide two methods for limiting the data in an analysis. A filter is always applied to a column before any selection steps are applied. Steps are applied in their specified order. Filters and selection steps differ in various ways:
Filters are applied directly to columns before the query is aggregated. Filters affect the query and thus the resulting values for measures. For example, suppose that you have a list of members in which the aggregate sums to 100. Over time, more members meet the filter criteria and are filtered in, which increases the aggregate sum to 200.
Selection steps are applied after the query is aggregated and affect only the members displayed, not the resulting aggregate values. For example, suppose that you have a list of members in which the aggregate sums to 100. If you remove one of the members using a selection step, then the aggregate sum remains at 100. Selection steps are per column and cannot cross columns.
Together with the columns that you select for an analysis, filters and selection steps determine what the results contain. Based on the filters and selection steps, only those results that match the criteria are shown. For example, depending on the industry in which you work, you can use filters and selection steps to learn who are the top ten performers, what are the dollar sales for a particular brand, which are the most profitable customers, and so on.
Another kind of filter, called a prompt, can apply to all items in a dashboard. You can use prompts to complete selection steps and filters at runtime. See Prompting in Dashboards and Analyses.
Oracle BI Enterprise Edition provides the Filters view and Selection Steps view, which you can add to an analysis to display any filters or selection steps applied to the analysis. Adding these views can help the user understand the information displayed in the analysis. See Adding Views for Display in Dashboards.
Filters and selection steps are applied on a column-level basis and provide two methods for limiting the data in an analysis.
A filter is always applied to a column before any selection steps are applied. Steps are applied in their specified order. Filters and selection steps differ in various ways.
Filters
You can apply filters directly to attribute columns and measure columns. You must apply filters before the query is aggregated and affect the query and thus the resulting values for measures. For example, suppose that you have a list of members in which the aggregate sums to 100. Over time, more members meet the filter criteria and are filtered in, which increases the aggregate sum to 200.
Selection Steps
Selection steps are applied after the query is aggregated and affect only the members displayed, not the resulting aggregate values. For example, suppose that you have a list of hierarchical members in which the aggregate sums to 100. If you remove one of the members using a selection step, then the aggregate sum remains at 100.
You can create selection steps for both attribute columns and hierarchical columns. Selection steps are per column and cannot cross columns. Because attribute columns do not have an aggregate member, the use of selection steps versus filters for attribute columns is not as distinctive as for hierarchical columns. While measure columns are displayed in the Selection Steps pane, you cannot create steps for them so steps do not affect them. Measures are used to create condition steps for attribute and hierarchical columns, such as Sales greater than $1 million.
You can use a filter on a related attribute column to affect the display of members in a hierarchical column.
For example, suppose a hierarchical column contains the levels Year, Quarter, and Month. Suppose that a filter exists on the attribute column that corresponds to the Year hierarchy level. If you create a filter on Year to limit it to 2008 and 2009, then when the hierarchical column is displayed in a view, only those two years are visible. This functionality depends on the way that the logical columns have been defined in the business layer of the subject area in the Oracle BI Administration Tool.
As you specify which data members to include in an analysis, you create selections of data from the data source.
Each selection specifies the criteria for a set of members for a particular column, such as Product or Geography. Each selection consists of one or more steps. A step is an instruction that affects the selection, such as add Product members whose values contain the text ABC. The order in which steps are performed affects the selection of data. Each step acts incrementally on the results from previous steps, rather than acting on all the members for that column.
You can view these selection steps in the Selection Steps pane. Steps are created using the following means:
When you add a column to an analysis, a selection step is created automatically to start with all members, unless you explicitly add specific members. As you drag and drop column members in the Results tab to add to the analysis, steps are also created automatically. For example, suppose that you drag and drop the FY2007 and FY2008 members from the Year hierarchical column to a pivot table. The selection step Add FY2007, FY2008 is created.
As you add groups and calculated items, steps are created automatically.
When you use right-click interactions (such as Add Related or Keep Only) to refine the selection of data for a particular hierarchical column or attribute column, steps are created automatically. To remove these selection steps, use right-click interactions such as Remove Group or Remove Calculated Item. See Right-Click Interactions in Views.
You can create steps directly using the Selection Steps pane, to refine the selection of data for a particular hierarchical column or attribute column. You can display the Selection Steps pane from various places including the Results tab, the Criteria tab, and some view editors.
Selection steps are one of the following types:
Explicit list of members — A step can include a list of members for a column, such as Boston, New York, Kansas, South. For hierarchical columns, the members can be from different hierarchy levels. For attribute columns, the members are from only that column.
Condition step — A step can specify that members are selected from a column based on a condition, which can be one of various types including based on measures or on top/bottom values. This member list is dynamic and determined at runtime.
When working with selection steps, if you search for members in hierarchical columns that are non-text (for example, date or time), then the search will yield no results.
Based on hierarchy step — A step for hierarchical columns that enables you to select the type of relationship with which to select members. You can select a family relationship (such as children of or parent of), a specific hierarchy level (for level-based hierarchies only), or a level relationship (for level-based hierarchies only).
Groups and calculated items — A step can include a group or calculated item. You can use groups and calculated items only with Add steps; you cannot use them in Keep Only or Remove steps.
You create steps in the Selection Steps pane, which you can display in various places.
You create a selection step to provide the instructions for specifying the criteria for selections of data from the data source. When you add a column to an analysis, an implicit Start with all members step is added. The "all" implies all the members of the column after filters are applied.
For example, you can create a step to specify criteria for the following members in an Office column: Baltimore, Austin, and Athens.
Creating selection steps in the Results tab allows users to choose the data most important to them.
Selection steps are automatically created when you use the right-click interactions (such as Add Related or Keep Only) to refine the selection of data for a particular hierarchical column or attribute column in a view. See Right-Click Interactions in Views.
After you add selection steps to the analysis, you can go to the Results tab of the Analysis editor and add the Selection Step view to the analysis. If you add the Selection Steps view, at runtime the user can view the selection steps that are applied to the analysis. See the Selection Steps editor of the Results tab.
You can edit existing selection steps in an analysis.
Use the Selection Steps pane to make changes to selection steps.
Saving selection steps as a group object lets them be reused in multiple places.
If you have created a set of selection steps, then you can save and reuse the set as a group object. SeeSaving Groups and Calculated Items as Inline or Named.
If your repository is configured for double columns, then you can create a selection step on a double column.
To create a selection step on a double column, select the display values for that column and the step is automatically evaluated using the code values that correspond to those display values.
If you use double columns, then use care with the New Calculated Item dialog. You can include a positional operator in the custom formula for the calculated item, such as $1, which specifies the column from the first row in the data set. When you include a positional operator, the display values cannot be mapped to the code values when evaluating the formula.
You can create a named or inline filter in columns to display specific data.
If your repository is configured for double columns, and you want to use an operator other than is equal to / is in, is not equal to / is not in, or is between and specify code values rather than display values, then you should explicitly choose the code column rather than the display column. See Understanding the Double Column Feature.
Use the following procedure to open and edit a saved filter.
If you edit and save a named filter, the changes that you make to the filter are propagated to wherever the filter is used.
This SQL function allows you to add a non-standard filter.
This section provides the following topics on working with the EVALUATE_PREDICATE function:
See Logical SQL Reference Guide for Oracle Business Intelligence Enterprise Edition.
You can add an EVALUATE_PREDICATE function as an inline filter clause.
You cannot use this function with hierarchical columns. Use this function when you cannot create the appropriate filter clause with the Oracle BI EE filter operators. This function is intended for database functions with a return type of Boolean, and can be used only for SQL functions. Support for EVALUATE_PREDICATE does not extend across all multidimensional data sources. Also, you cannot use EVALUATE_PREDICATE with XML data sources.
To add an EVALUATE_PREDICATE function as an inline filter clause, you must have been granted the Add EVALUATE_PREDICATE Function privilege by the administrator.
Example
The following is an example of how you can use the EVALUATE_PREDICATE function. This example requests that Products.P4 Brand values be greater than 6 characters. After it is run, this example returns any rows where the length of the data in the P4 Brand column is greater than 6 characters (for example, BizTech and HomeView).
SELECT
0 s_0,
"A - Sample Sales"."Products"."P3 LOB s_1,
"A - Sample Sales"."Products"."P4 Brand" s_2,
"A - Sample Sales"."Base Facts"."1- Revenue" s_3
FROM "A - Sample Sales"
Where EVALUATE_PREDICATE('length(%1)>6',"A - Sample Sales"."Products"."P4 Brand").
ORDER BY 1,2,3
This procedure describes how to add the EVALUATE_PREDICATE function to an inline filter.
You cannot use this function with hierarchical columns. For more information see How Can I Use the EVALUATE_PREDICATE Function with a Filter? and Logical SQL Reference Guide for Oracle Business Intelligence Enterprise Edition.
If you want to filter data in an analysis, you can apply any named filter.
Use the following procedure to apply a named filter to an analysis.
Shared Folders/2. Functional Examples/Filters/A - Sample Sales/Demo.Combining and grouping column filters with AND and OR Boolean operators enables you to create complex filters without requiring you to know SQL statements.
Grouping or combining column filters enables you to establish the precedence in which Oracle BI EE filters an analysis.
If you want to group filters, then the filter must contain three or more filter items.
You can create a filter based on the values that are returned by another analysis.
Any saved analysis that returns a column of values can be used to filter the matching column in an analysis.
You can create and edit the logical SQL WHERE clause to be used as a filter.
While generally not necessary, this feature is available for users who want advanced filtering capability. For descriptions of SQL clauses, see Oracle Fusion Middleware LogicalSQL Reference Guide for Oracle Business Intelligence Enterprise Edition.
After you convert a filter to SQL statements, you can view and edit the filter item as SQL statements in the Advanced SQL Filter dialog, only. You can no longer view and edit the filter in the Edit Filter dialog.
Calculated measures are derived from other measures and created by using formulas.
You cannot add calculated measures to direct database queries or combined requests.
To create a calculated measure:
Perform one of the following actions:
To create a calculated measure for data views that contain columns within the Compound Layout, click the New Calculated Measure button on the Analysis editor: Results tab.
To create a calculated measure for a specific data view within the Compound Layout, edit the specific data view, and then click the New Calculated Measure button on the Data View editor of the Results tab.
Complete the New Calculated Measure dialog.
Click the OK button.
To edit a calculated measure:
You can edit a calculated measure from the Criteria tab of the Analysis editor.
You can create a group or calculated item as a way to display data in a heat matrix, table, pivot table, trellis, or graph.
Groups and calculated items allow you to add new "members" to a column, when those members do not exist in the data source. These members are also known as "custom members."
A group is a static list of members that you select or a static or dynamic list that is generated by selection steps. A group is represented as a member. You can drill in a group that was created for a hierarchical column but not in one that was created for an attribute column.
A group uses the existing aggregation function of the measure column with which it is displayed. The aggregation is performed up from the lowest detail level in the Oracle BI Server, but no values are double-counted.
A calculated item is a computation between members, which is represented as a single member that cannot be drilled. When you create a calculated item, you add a new member in which you have selected how to aggregate the item, such as Sum or Average or a custom formula. The calculation is performed at the aggregated level, not at the lowest detail level.
Both groups and calculated items become selection steps for the entire analysis when you select the All Views option while creating the group or calculated item. Therefore, they apply to all views for that analysis. These groups and calculated items can be saved as inline or named objects. For information, see Saving Objects as Inline or Named.
If you create a group or calculated item for a specific view by selecting the Current View option, the group or calculated item only applies to the specific active view.
A group (also known as a "saved selection" in other products) is a user-defined member of a column.
A group can be a list of members or a set of selection steps that can be executed to generate a list of members. All the members must be from the same attribute column or hierarchical column, and in a hierarchical column, members can be from different hierarchy levels. Groups are always displayed at the bottom of the column list in the order in which they were added (as shown in the Selection Steps pane). Groups can contain members or other groups. You can create a custom group and add the custom group to a column within a view.
You can save a group to the catalog and reuse it. For example, you can apply a group to analysis and dashboard column prompts or variable prompts. If a group is applied to a prompt, then the prompt presents either the group as a choice list option or members of the group as choice list options to the user at runtime. See Overriding a Selection Step With a Column Prompt for information on overriding selection steps with prompts when the user selects groups or column members.
A calculated item is a calculation between members, which is represented as a single member.
A calculated item enables you to override the default aggregation rule that is specified in the Oracle BI repository, and for an existing analysis, the aggregation rule chosen by the designer. You can define a calculated item using a custom formula (which is the default) or by combining selected members with a function (for example, SUM).
A calculated item is a user-defined member of a column. A calculated item can contain members or other calculated items. Calculated items are always displayed at the bottom of the column list in the order in which they were added (as shown in the Selection Steps pane). You can save a calculated item to the catalog and reuse it.
A calculated item is useful when you want to view and manipulate a set of members as a single entity. For example, you might define calculated items for:
Key accounts in a geographic region
High-end products
Non-standard time periods, such as the first three weeks in September
You can create calculated items for columns in various places. Calculations differ from the default aggregation rules that are applied to measures. See Adding Totals to Tables and Pivot Tables. Internally, calculated items are processed as SQL SELECT statements, and the indicated functions are performed on the result set. See Oracle Fusion Middleware LogicalSQL Reference Guide for Oracle Business Intelligence Enterprise Edition .
Use a group or calculated item to add new "members" to a column.
For example, you can review how much revenue was generated for mobile devices and compare that number to other product types. You can create a group called Mobile Devices for the Product column that includes Flip Phones and Smart Phones. Use the following procedure to create a calculated item or group.
Check with the administrator about implementing one of the following possible solutions:
Explicitly specify the aggregation rule for the measure in the repository.
Create the appropriate group of values as a dimension member in the Oracle OLAP analytic workspace.
You can update groups and calculated items to present the most useful information to users.
You can edit groups and calculated items in various ways:
In the Selection Steps pane, click the link for the calculated item or group, then click Edit to display the appropriate dialog.
If you have saved the object to the catalog, then select the object in the Catalog pane and click Edit to display the appropriate dialog.
In a heat matrix, table, pivot table, or trellis (on an outside edge), right-click the group or calculated item and select Edit Group or Edit Calculated Item.
The value of a group or calculated item might be affected by filters and selection steps in several ways:
Filters — A group or calculated item is evaluated using only those members that have not been removed using filters. For example, if you have a calculated item for SUM (EAST + WEST) but WEST is removed through a filter, then only the EAST sum is included for the calculated item. If all members have been removed, then a null value is returned, which shows as an empty cell in a heat matrix, table, pivot table, or trellis.
Selection steps — When you create selection steps, you can add a group or a calculated item in a step. Subsequent Keep Only or Remove steps might reference members that were included in the group or calculated item.
A group list is affected by members that are kept or removed in subsequent steps, but the group outline value remains the same. For example, suppose the MyNewYork group contains Albany and Buffalo and its value is 100. Suppose Albany is removed in a later step. The value of the MyNewYork group remains at 100, but Albany is no longer listed with the group.
A calculated item is not affected by members that are kept or removed in subsequent steps.
If you remove a group or calculated item from all views that was created by using the Current View option button, the group or calculated item remains and will not be added to any new view that you subsequently add.
If you remove a group or calculated item from all views that was created by using the All Views option button, the group or calculated item remains and will be added to any new view that you subsequently add.
Consider the following if you are removing a group or calculated item by using the right-click menu:
From a view within a dashboard page — The calculated item or group will be removed only from the current view.
From a view within a view editor — The calculated item or group will be removed only from all views.
You can add a group to the same column on which it was created in another analysis.
Groups added to an analysis can be either a list of members or a set of selection steps. For information on these groups, see Saving Selection Steps as a Group Object.
To add the group, you can use the Results tab, or you can do so in the Catalog pane. You can also add a group using the following means:
In the Edit Member Step dialog, select Start with Group or Calculated Item in the Action box, then select the group from the Catalog pane in the Available list.
In the Selection Steps pane, click Then, New Step for the appropriate column, select Add Groups or Calculated Items, select Select Existing Groups and Calculated Items, and select the group in the resulting dialog.
As you work with groups and calculated items, you might want to "nest" them; that is, create a group within a group, for example.
The following list provides various scenarios for nesting groups and calculated items:
Groups can be nested; that is, they can include other groups. Nested groups are "flattened." For example, suppose that the my_favorite_countries group includes the my_favorite_cities group. When you display and expand the my_favorite_countries group in a table, you do not see the my_favorite_cities group. Instead, you see the member values of the my_favorite_cities group.
Calculated items can be nested; that is, they can include other calculated items.
Groups cannot contain calculated items nor can calculated items contain groups.
When you work with selection steps:
You can save selection steps that include groups or calculated items as either a series of steps whose results are generated at runtime or as results that are static and are redisplayed each time.
You can apply a group that is a saved selection of steps, using the Catalog pane. If you do so when the saved selection contains a step for a calculated item, then you can only add the members of the group. You cannot add the group itself.
To understand calculated items, you must have a basic understanding of SQL.
The examples and explanations in this section assume that you have a basic understanding of SQL statements and their syntax. The syntax shown in these examples applies to the Custom Formula function in the New Calculated Item dialog. The examples are hypothetical. Not all possible calculated items are shown.
Example 6-1 Obtaining the Value of the Current Measure
This example shows the code required to obtain the value of the current measure, such as dollar sales, for each of the products SoftDrinkA, SoftDrinkB, and SoftDrinkC, and adds the values.
This is equivalent to selecting Sum from the Function list, and then typing or clicking 'SoftDrinkA','SoftDrinkB','SoftDrinkC' to add them to the Function field.
sum('SoftDrinkA','SoftDrinkB','SoftDrinkC')Example 6-2 Obtaining the Minimum Current Measure
This example shows the code required to obtain the minimum current measure, such as dollars in sales, for SoftDrinkA or SoftDrinkB, whichever is lower.
min('SoftDrinkA','SoftDrinkB')
In this example and the previous one, each functional calculated item is performed for each member in the outer layer, such as the Product layer. For example, if Year and Product are positioned on an axis, and one of the preceding calculated items is built on the Product layer, then the results are computed per year.
Example 6-3 Obtaining the Values of Each Item in the Outer Layer
This example shows the code required to obtain the values for each item in the outer layer, such as Year and Product, and adds them.
Instead of specifying a named item for an attribute column, such as SoftDrinkA, you can specify $n or $-n, where n is an integer that indicates the item's row position. If you specify $n, then the measure is taken from the nth row. If you specify $-n, then the measure is taken from the nth to the last row.
For example, for dollar sales, $1 obtains the measure from the first row in the data set, and $-1 obtains the measure from the last row in the data set.
sum(*)Example 6-4 Obtaining the Values of Measures and Summing Them
This example shows the code required to obtain the current measure, such as dollar sales, of the item from the first, second, and third rows, and sums them.
sum($1,$2,$3)Example 6-5 Adding Sales Values
This example shows the code required to add sales of SoftDrinkA, SoftDrinkB, and SoftDrinkC. The two calculated items shown in the example are equivalent. That is, Sum is the default function; therefore, it can be omitted.
'SoftDrinkA' + 'SoftDrinkB' + 'SoftDrinkC' sum('SoftDrinkA','SoftDrinkB','SoftDrinkC')Example 6-6 Adding Sales Values and Returning the Maximum
This example shows the code required to add sales of SoftDrinkA with sales of diet SoftDrinkA, then adds sales of SoftDrinkB with sales of diet SoftDrinkB, and returns the maximum of these two amounts.
max('SoftDrinkA' + 'diet SoftDrinkA', 'SoftDrinkB' + 'diet SoftDrinkB')