2 Creating Analyses

What Are Analyses?

An analysis is a query against an organization's data that provides answers to business questions. A query contains the underlying SQL statements that are issued to the Oracle BI Server.

Analyses let you explore and interact with information by visually presenting data in tables, graphs, pivot tables, and so on. You can save, organize, and share the results of analyses.

Analyses that you create can be saved in the Oracle BI Presentation Catalog and integrated into any Oracle BI EE dashboard. Analyses can be enhanced through features such as graphs, result layout, calculated items, and drilling.

What Are Subject Areas and Columns?

A subject area contains folders, measure columns, attribute columns, hierarchical columns, and hierarchy levels that represent information about the areas of an organization's business or about groups of users with an organization. Subject areas usually have names that correspond to the types of information that they contain, such as Marketing Contracts, Service Requests, and Orders.

A subject area corresponds to the presentation layer in an Oracle BI metadata repository. In a repository, the subject area is the highest-level object in the presentation layer and represents the view of the data that end users see when they create or edit an analyses.

Individuals who design and build metadata repositories (such as a Business Intelligence strategist, metadata provider, or ETL developer) create subject areas using the Oracle BI Administration Tool. Generally, rather than creating one large subject area for their company's data, they create multiple smaller subject areas. This enables them to provide a particular group of users or a particular area of a company with the most important data that they need in one small subject area and the less important data in one or more related subject areas created from the same business model layer. Having these smaller subject areas makes it easier for users to find the data they need. It also makes it easier to maintain the data. For more information on creating subject areas, see Oracle Fusion Middleware Metadata Repository Builder's Guide for Oracle Business Intelligence Enterprise Edition.

Columns contain the individual pieces of data that an analysis will return. Columns usually have names that indicate the types of information that they contain, such as Account or Contact. Together with filters and selection steps, columns determine what data an analysis will contain.

When you create a new analysis, filter, or dashboard prompt, you first select the subject area with which you want to work. This is known as the primary subject area and is displayed in the "Subject Areas pane". If, as you work, you find that you need more data, you can add additional subjects areas that are related to the primary subject area that you have chosen. (You can add related subject areas only if they are available for the primary subject area and only if you have permission to access them.)

For an analysis to return data, you must select at least one column to include in the analysis.

How Are Columns Indicated Visually?

Each type of column is indicated by its own icon in places such as the Subject Areas pane and Layout pane. You can expand level-based hierarchies and see their levels. Parent-child hierarchies are shown as hierarchical columns that have no levels. Figure 2-1 shows the icons and names of various columns.

Figure 2-1 Column Types With Their Icons

Understanding the Double Column Feature

Oracle BI EE provides a feature called double columns. When a repository is configured for the double column feature, column data includes a display column that has a code column mapped to it (that is, it has double columns). A display column contains the display values for the column data, for example, Excellent, Good, and Poor. A code column contains code values that uniquely identify display values and are consistent across users or locales, for example, the code values 1 (uniquely identifying Excellent), 2 (uniquely identifying Good), and 3 (uniquely identifying Poor).

When Oracle BI EE processes a double column, for example, as part of the criteria of an analysis or as the basis for a filter, it generates and issues SQL statements to the Oracle BI Server that use code values rather than display values, thereby making the filter language independent.

The double column feature lets you:

• Build internationalized analyses that are automatically filtered by language independent codes. (In previous releases, filters were not language independent.) For example, you can build one filtered analysis that can be used by both French-language users and English-language users.

• Build common analyses that can be shared among groups even if the groups require different display values. For example, you can build a common analysis that displays for a Status field the values Excellent, Good, and Poor to one group, and Superb, Okay, and Bad to another group.

• Change display values without breaking existing analyses. For example, suppose that you have an analysis that is filtered on the display value Excellent. If it is a double column, then the filtering will be performed on its code column with the code value for "Excellent" rather than the display value of "Excellent." This means that you can change the display value Excellent to Superb without breaking the existing analysis.

In addition, if your organization allows the display of code values within Oracle BI EE, you can use code values rather than the display values in some dialogs, such as the "New Filter dialog". This means, for example, when specifying the values to use when applying a filter, you can specify code values rather than display values.

Before you can take advantage of the double column feature, your administrator must configure your repository by mapping code columns to display columns. Check with the administrator to see if your repository is configured for double columns.

What Is the Analysis Editor?

The "Analysis editor" lets you explore and interact with information by visually presenting data in tables, graphs, pivot tables, and so on. You can include the views that you create in an analysis for display in dashboards.

The Analysis editor contains the following tabs:

• Criteria tab — Lets you specify the criteria for an analysis, including columns, and filters. You can specify the order in which the results should be returned, formatting (such as headings, number of decimal places, styles such as fonts and colors, and conditional formatting), and column formulas (such as adding a Rank or Percentile function).

• Results tab — Lets you create different views of the analysis results such as graphs, tickers, and pivot tables. You can also add or modify selection steps.

• Prompts tab — Lets you create prompts that allow users to select values to filter an analysis or analyses on a dashboard. Prompts allow users to select values that dynamically filter all views within the analysis or analyses. You can also create prompts for use with selection steps, both for member selection steps and qualifying condition steps.

• Advanced tab — Lets you edit XML code and examine the logical SQL statement that was generated for an analysis. You can use the existing SQL statement as the basis for creating a new analysis.

The tabs of the Analysis editor are organized into various panes and areas. As you work, you will want to manage these panes to suit your needs. See "Managing Panes in the Analysis Editor Tabs".

You access the Analysis editor when you create (or edit) an analysis. See "Creating New Analyses".

What Is the Process for Constructing Analyses?

The process for constructing an analysis includes the following steps:

1. "Creating New Analyses"

2. "Specifying the Criteria for Analyses"

3. "Displaying the Results of Analyses"

4. "Adding Prompts to Analyses"

5. "Examining the Logical SQL Statements for Analyses"

6. "Saving Analyses"

Creating New Analyses

This procedure is a step in the process for constructing an analysis. For more information, see "What Is the Process for Constructing Analyses?"

To create a new analysis:

1. In the global header, click New, then Analysis, then one of the following options:

   • Select a subject area.

     The Analysis editor is displayed. You can now specify the criteria for the analysis. See "Specifying the Criteria for Analyses".

   • Create Direct Database Request.

     For information, see "Working with Direct Database Requests".

   • Create Analysis from Simple SQL.

     The "Analysis Simple SQL Statement dialog" is displayed in which you enter SQL statements for creating an analysis. The results of the analysis can be displayed and manipulated within the Analysis editor, and subsequently incorporated into dashboards and agents.

Specifying the Criteria for Analyses

This procedure is a step in the process for constructing an analysis. For more information, see "What Is the Process for Constructing Analyses?"

You use the "Analysis editor: Criteria tab" to specify the criteria for an analysis, including columns, filters, and selection steps. You also can specify:

• The default order in which columns are to be displayed in the analysis results

• The default sorting for the values that are displayed in views

• The default formatting (such as headings, number of decimal places, conditional formats, and system-wide defaults)

• Column formulas (such as adding a Rank or Percentile function)

• The aggregation rules for column totals

To specify the criteria for an analysis:

1. In the Criteria tab, select the columns to be included in the analysis by doing one of the following:

   • Double-clicking the columns in the "Subject Areas pane".

   • Dragging and dropping the columns from the Subject Areas pane to the "Selected Columns pane".

     To select:

     • Multiple contiguous columns, press and hold the Shift + Ctrl keys, then click each column that you want.

     • Multiple non-contiguous columns, press and hold the Ctrl key, then click each column that you want.

   Note:

   In general, the analysis should contain at least one measure column. Measure columns are the key additive measurements of business performance, such as dollar sales per store, or the number of service requests opened and closed each day. An analysis without any measure columns generally is not meaningful, and can cause poor query performance or unexpected results. If you want to build an analysis without any measure columns, then first consult the administrator.

   The selected columns are displayed in a box in the Selected Columns pane. Each column box has two sections. The upper section shows the name of the folder that contains the column, for example, Customers. The lower section shows the name of the column, for example, Customer Name.

   If you want to:

   • Add or remove related subject areas from which to select columns, click the Add/Remove Subject Areas toolbar button in the Subject Areas pane to display the "Add/Remove Subject Areas dialog".

     If you add a related subject area but do not add any columns from that subject area to the analysis, then the subject area is not related to the analysis after you close and re-open the analysis.

   • Refresh the content in the Subject Areas pane, click the Refresh toolbar button on the Subject Areas pane or click the arrow beside the button.

     Clicking the button executes the default behavior of Refresh Display. Clicking the arrow allows you to select Refresh Display or Reload Server Metadata to refresh the subject area's metadata.

     For more information about these options, see the "Subject Areas pane".

2. Modify the columns or levels of hierarchical columns as needed using the Selected Columns pane:

   • Click the Options button to the right of a column name in the Selected Columns pane to display options to:

     • Specify the sort order for columns. (You cannot specify the sort order for hierarchy levels.)

       For more information, see "Sorting Data in Views".

     • Edit formulas for attribute columns and measure columns, including customizing headings, and specifying the aggregation rule. (You cannot customize headings, specify the aggregation rule, or edit the formulas for hierarchical columns or for hierarchy levels.)

       For more information, see "Editing the Formula for a Column".

     • Edit column properties to control the formatting and interaction of columns and hierarchy levels.

       For more information on applying formatting, see "Applying Formatting to a Column".

     • Add filters for attribute columns and measure columns. (You cannot add filters for hierarchical columns or hierarchy levels.) For more information, see "Creating or Editing Column Filters".

     • Delete the columns from the analysis. (You cannot delete hierarchy levels.)

   • Click the Remove all columns from criteria toolbar button in the Selected Columns pane to remove all columns from the analysis.

   • Click the Combine results based on union, intersection, and difference operations toolbar button in the Selected Columns pane to combine the results of two or more analyses into a single result. For more information, see "Combining Columns Using Set Operations".

   • Use the Drag Column buttons in the Selected Columns pane to place the columns in the default order that you want them to be displayed in the analysis results.

3. Add and edit inline filters as needed using the "Filters pane".

   For more information, see "Creating or Editing Column Filters".

4. Create or edit selection steps as needed using the "Selection Steps pane".

   For more information, see "Working with Selections of Data".

5. Add named filters, calculated items, and groups from the Oracle BI Presentation Catalog as needed using the "Catalog pane".

6. Use the buttons on the toolbar for the Criteria tab, as needed, to show or hide the Filters pane, to show or hide the Selections Steps pane, and to edit the properties of the analysis, such as the type of message (default or custom) to be displayed if no results are available.

You can now add views to the analysis. See "Displaying the Results of Analyses".

Editing the Formula for a Column

You can edit the formulas for attribute columns and measure columns when you specify the criteria for an analysis. This editing affects the column only in the context of the analysis and does not modify the formula of the original column in the subject area. You can also customize table and column headings and specify the aggregation rule for column totals. (This functionality is not available for hierarchical columns.)

A column formula specifies what the column values represent. In its most basic form, such as "Sales Measures"."Dollars", a column takes the data from the data source as is. You can edit the formula to add functions, conditional expressions, and so on. This allows you to present analysis results in a variety of ways. For example, suppose you wanted to do some what-if analysis and show what the sales dollars would be by region if you increased them by 10%. You can do this by changing the formula for the Dollars column to show the sales dollars increased by 10%. Figure 2-2 shows an analysis that shows the Dollars column (which shows the sales dollars in your data source) and the Dollars Increased by 10% column, where the formula for the Dollars column was edited to show sale dollars increased by 10%.

Figure 2-2 Analysis Showing Dollars and Dollars Increased by 10%

To edit the formula of a column:

1. In the "Selected Columns pane", click the Options button beside the column whose formula you want to edit and select Edit Formula. The "Edit Column Formula dialog" is displayed.

2. Use the "Edit Column Formula dialog: Column Formula tab" to perform various tasks such as creating customized headers and creating or editing the formula for the column. You can build a simple mathematical formula using operator and character buttons, such as "Sales Measures"."Dollars"*1.10.

3. Optionally, use the "Edit Column Formula dialog: Bins tab" to combine values for the column into sets.

4. Click OK.

   The column formula is saved with the analysis with which it is used.

Related Topics

"What Are Analyses?"
"Specifying the Criteria for Analyses"

Displaying the Results of Analyses

This procedure is a step in the process for constructing an analysis. For more information, see "What Is the Process for Constructing Analyses?"

You use the "Analysis editor: Results tab" to add different views of the results such as graphs, tickers, and pivot tables. For a list of the views that you can add, see "What Types of Views Are Available?"

When you create an analysis and display the Results tab, you see in the "Compound Layout" a title view and either a table or pivot table view by default, based on the following:

• If the analysis contains only attribute columns and measure columns, then a table is displayed by default.

• If the analysis contains at least one hierarchical column, then a pivot table is displayed by default.

The administrator might have configured different views to display by default in the Results tab.

You can combine views and position them anywhere in the Compound Layout. For example, you can create side-by-side pivot tables that reflect different views of the data, graphs that allow you to explore interrelationships in depth, and filters that limit the results.

Together all of these views are called a compound layout. You can create additional compound layouts, as described in "Creating Additional Compound Layouts".

To display the results of an analysis:

1. Click the Results tab.

   The results of the analysis are displayed in a table or pivot table.

2. (Optional) Edit the table or pivot table or add additional views. For more information, see "Adding Views for Display in Dashboards".

No Results
The specified criteria didn't result in any data.
This is often caused by applying filters and/or selections that are too restrictive or that contain incorrect values.
Please check your Analysis Filters and try again.
The filters currently being applied are shown below.

Adding Prompts to Analyses

This procedure is a step in the process for constructing an analysis. For more information, see "What Is the Process for Constructing Analyses?"

You use the "Analysis editor: Prompts tab" to create prompts that allow users to select values to filter an analysis. Prompts allow users to select values that dynamically filter all views within the analysis.

To add a prompt to an analysis:

1. Click the Prompts tab.

2. Add the prompt, as described in Chapter 6, "Prompting in Dashboards and Analyses."

Examining the Logical SQL Statements for Analyses

This procedure is an advanced step in the process for constructing an analysis. For information, see "What Is the Process for Constructing Analyses?"

You use the "Analysis editor: Advanced tab" to examine the XML code and logical SQL statement that is generated for an analysis and optionally create a new analysis based on that SQL statement. Generally you need not use the features of this tab, because the vast majority of functionality for working with analyses is provided through the user interface. The following list provides examples of situations in which you might want to examine SQL statements:

• You can use the Prefix section to override any user variable or session variable that has been marked as available for updating. You can specify multiple variables to update with one line of code.

  To override variables, use the following syntax:

  SET VARIABLE var-name=value

  For example, you can set the variables that are shown in the following code line:

  SET VARIABLE "My Variable"=4, DISABLE_CACTHE_HIT = 1, LOGLEVEL = 2;

  For information on variables, see "Where Can I Reference Variables?"

• You can temporarily change the logging level for an analysis for troubleshooting, even when logging is turned off for analyses. In the Prefix section of the Advanced tab, you can specify the following:

  SET VARIABLE LOGLEVEL=4;

  This specification runs the analysis at level 4, which facilitates advanced troubleshooting. The default level is 0, which indicates no logging. You can view the logs using the View Log link on the "Administration: Manage Sessions page".

  See Oracle Fusion Middleware Metadata Repository Builder's Guide for Oracle Business Intelligence Enterprise Edition for information on logging levels.

• You can enter your own logical SQL statements. Entering your own statements eliminates many features of Oracle BI EE (such as hierarchical columns, selection steps, groups, and formatting), but allows you to use functions such as SET operations.

• You can create a new analysis using the SQL statements from an existing analysis as your starting point.

Before working with the Advanced tab, keep the following important points in mind:

• This procedure is only for advanced users and developers that have the appropriate responsibilities to access the Advanced tab. It is assumed that you understand advanced SQL statements, have expertise working with the Oracle BI Server metadata, are familiar with the SQL information in Appendix A, "Logical SQL Reference", and understand the content and structure of the underlying data sources.

• This tab provides the Advanced SQL Clauses area, which allows you to add clauses to the SQL statements and other similarly advanced features. These features, with the exception of the ability to specify a prefix, are disabled for analyses that contain hierarchical columns, member selections, or groups.

• The links at the top of the tab allow you to download analysis results into Microsoft Excel. You might be unable to download analysis results based on the security features that have been configured at your organization. For information, contact your administrator.

To edit the XML code or examine the SQL statement that is generated for an analysis:

1. Click the "Analysis editor: Advanced tab".

2. Use the links that correspond to the analysis name in the Referencing the Results area at the top of the tab to:

   • Display pages that contain links for working with the results of the analysis.

   • Download a file for working with the results of the analysis in Excel. For information, see "Integrating an Analysis with Microsoft Excel's Internet Query Feature".

3. Use the fields in the Analysis XML area to view and modify the XML code, and click Apply XML.

   If you modify the XML code, then you affect the analysis as it is saved in the Oracle BI Presentation Catalog.

4. Use the read-only box in the SQL Issued area to examine the SQL statement that will be sent to the Oracle BI Server when the analysis is executed.

   If you want to create a new analysis using the SQL statement from the current analysis as the starting point, then click the New Analysis button. Any hierarchical columns, selection steps, groups, or formatting that are specified in the current analysis will be removed.

5. Depending on the content of the analysis, use the available fields in the Advanced SQL Clauses area to change the subject area, add GROUP BY or HAVING clauses, and specify DISTINCT processing and a prefix. Click Apply SQL to activate your changes.

   Note:

   Use care when clicking the Apply SQL button. When you do, Oracle BI EE creates a new analysis based on the SQL statement that you have added or modified. Therefore, you will lose all views, formatting, and so on that you had previously created for the analysis. The XML code will also be modified for the new analysis.

Saving Analyses

This procedure is a step in the process for constructing an analysis. For more information, see "What Is the Process for Constructing Analyses?"

You can save an analysis to a:

• Personal folder, from which only you can access it.

  Your top-level personal folder is called My Folders. Every user with a unique user name has a folder called My Folders. This is designed to hold the analyses that you run most often, and other content that you access frequently.

  When you click the Refresh Display link at the bottom of the pane, the analysis is listed under the folder in which you saved it.

• Shared folder, from which users with permission to access that folder can access it.

• Lotus Notes database by either:

  • Saving the analysis to a Web archive file (file extension .mht), and then uploading the file to the Lotus Notes database.

  • Saving the analysis and scheduling it to be sent by e-mail automatically to a specific address on a Lotus Notes server using an agent. The Lotus Notes server can then process the e-mail and write it to the database.

To save an analysis:

1. In the Analysis editor, click the Save Analysis toolbar button to display the dialog to save the analysis.

2. If you want to save the analysis to a personal or shared folder:

   1. In the Save In box, select the personal or shared folder in which to save the analysis.

   2. In the Name field, enter a name for the analysis, such as forecasted_sales.

   3. Click OK.

3. If you want to save the analysis to a Lotus Notes database using a Web Archive file:

   1. In the Save In box, select the folder in which to save the analysis.

   2. In the Name field, enter a name for the analysis, including an .mht file extension, such as forecasted_sales.mht.

   3. Click OK.

   4. Upload the .mht file to the Lotus Notes database.

4. If you want to save the analysis to a Lotus Notes database using an agent:

   1. In the Save In box, select the folder in which to save the analysis.

   2. In the Name field, enter a name for the analysis, such as forecasted_sales.

   3. Click OK.

   4. Create the agent, scheduling it to be sent by e-mail to a specific address on a Lotus Notes server.

      For more information on creating an agent, see "Creating Agents".

Creating Agents from Analyses

You can create an agent directly from an analysis. When you create an agent using this method, Oracle BI EE does the following:

• Creates a condition based on the analysis and adds the condition to the "Agent editor: Condition tab"

• Adds the analysis as the content delivery on the "Agent editor: Delivery Content tab"

For more information on agents, see Chapter 8, "Delivering Content."

To create an agent from an analysis:

1. Locate the analysis from which you want to create an agent using one of the following methods:

   • Open the analysis, click the "Analysis editor: Results tab" and then the Schedule toolbar button.

     The analysis is saved and then the "Agent editor" is displayed.

   • Navigate to the analysis on the "Catalog page", click the More list, and then click the Schedule option.

     The "Agent editor" is displayed.

2. Complete the following tabs of the Agent editor:

   • "Agent editor: General tab"

   • "Agent editor: Schedule tab"

   • "Agent editor: Condition tab"

   • "Agent editor: Delivery Content tab"

   • "Agent editor: Recipients tab"

   • "Agent editor: Destinations tab"

   • "Agent editor: Actions tab"

3. Save the agent.

Editing Analyses

To edit an analysis:

1. In the global header, click Catalog to display the "Catalog page".

2. Navigate to the analysis that you want to edit and click the Edit link. The analysis is displayed in the "Analysis editor".

3. Make the desired changes.

4. Save the analysis.

About Embedding an Analysis in a Dashboard

Embedding an analysis in a dashboard causes it to execute automatically and display the results within the dashboard. This provides access to current results. For example, if you are a sales executive whose company captures sales data on a daily basis, then you might want to have the dollar volume of product that was sold today be displayed on the front page of your dashboard.

You can embed previously created analyses from the Oracle BI Presentation Catalog by using the Dashboard editor. For information about the Dashboard editor, see "Adding Content to Dashboards".

Working with Direct Database Requests

Users with the appropriate privileges can create and issue a direct database request directly to a physical back-end database. The results of the request can be displayed and manipulated within the Analysis editor, and subsequently incorporated into dashboards and agents. This section includes the following topics:

• "Setting Privileges for Direct Requests"

• "Executing a Direct Database Request"

• "Seeing the Results of Direct Database Requests"

Using Variables

You can reference variables in a number of areas of Oracle BI Enterprise Edition, including in analyses, dashboards, KPIs, actions, agents, and conditions. For example, suppose that you wanted to create an analysis whose title displays the current user's name. You can do this by referencing a variable.

There are four types of variables that you can use:

• Session

• Repository

• Presentation

• Request

Where Can I Reference Variables?

You can reference variables in the following areas (but not all types of variables can be referenced in each area):

• Title views. See "Results tab: Title editor".

• Narrative views. See "Results tab: Narrative editor".

• Static text views. See "Results tab: Static Text editor"

• Filters. See "New Filter dialog" and "New EVALUATE_PREDICATE Function dialog".

• Column formulas. See "Edit Column Formula dialog: Column Formula tab".

• Conditional formatting conditions. See "Column Properties dialog: Conditional Format tab" and "New Condition dialog".

• Table and column headings in analyses. See "Column Properties dialog: Column Format tab".

• Direct database requests. See "Working with Direct Database Requests".

• Dashboard prompts and inline prompts. See "New Prompt dialog".

• Headers and footers for PDF output. See "Edit Footer or Header dialog"

• Link or image objects in a dashboard. See "Link or Image Properties dialog".

• Text objects in a dashboard. See "Text Properties dialog".

• Graphs to specify conditional formatting of graph data. See "Graph Properties dialog: Style tab" and "Style and Conditional Formatting dialog: Conditional Formatting tab".

• Gauge thresholds. See "Enter Expression dialog".

• Gauge limits. See "Customize Gauge Limit dialog".

• Agents. See the "Agent editor: Delivery Content tab".

• Actions to specify parameters. See "Create New Action dialog" and "Edit Parameter Mapping dialog".

• Conditions to specify parameters. See "New Condition dialog".

• Selection steps. See "New Condition Step dialog".

• KPIs to define thresholds. See "KPI editor: Thresholds page".

• KPIs included in a KPI watchlist. See "Add KPI dialog".

• URL fields in dialogs. See "Image Map Prompt Properties dialog".

For the syntax that you need to use to reference variables, see "What Is the Syntax for Referencing Variables?"

What Is the Syntax for Referencing Variables?

You can reference variables in analyses, dashboards, KPIs, and agents. How you reference a variable depends on the task that you are performing.

For tasks where you are presented with fields in a dialog, you need to specify only the type and name of the variable (not the full syntax), for example, referencing a variable in a filter definition.

For other tasks, such as referencing a variable in a title view, you specify the variable syntax. The syntax you use depends on the type of variable as described in Table 2-1.

You also can reference variables in expressions. The guidelines for referencing variables in expressions are described in Table 2-2.

"Market"."Region"=VALUEOF(NQ_SESSION."SalesRegion")

CASE WHEN "Hour" >= VALUEOF("prime_begin") AND "Hour" < VALUEOF("prime_end") THEN 'Prime Time' WHEN ... ELSE...END

"Market"."Region"=@{MyFavoriteRegion}{EASTERN REGION}

For the specific areas where you can reference variables, see "Where Can I Reference Variables?".

What Predefined Presentation Variables Are Available?

Table 2-3 contains a list of the predefined presentation variables that you can reference in analyses, dashboards, KPIs, and agents. (Note that the syntax for these predefined presentation variables omits the variables. qualifier, for example, @{session.locale} rather than @{session.variables.locale}.)

Example of Referencing a Variable in a Title View

Suppose that you have created a dashboard prompt called Region, which is based on the Region column and which creates a presentation variable called MyFavoriteRegion as shown in Figure 2-3.

Figure 2-3 Region Prompt

Suppose also that you have created an analysis that shows Dollars by Region and District. You have also added a filter on the Region column that is set to Is Prompted so that you can prompt the user for a region using this Region prompt.

You can reference the MyFavoriteRegion variable in the Title view so that the user's selection in the Region prompt is displayed in the title of the analysis. To do so, you enter the variable syntax @{variables.MyFavoriteRegion} in the Title field in the Title editor, as shown in Figure 2-4.

Figure 2-4 MyFavoriteRegion Variable Referenced in the Title View

Figure 2-5 shows the results on a dashboard page when a user selects EASTERN REGION in the Region prompt. Notice that the variable in the title has been updated to the user's selection, EASTERN REGION.

Figure 2-5 Results of Referencing My Favorite Region in the Title View