Editing Views

Applying Formatting to Tables and Pivot Tables

Green bar styling shows alternating rows or columns in a light green color. Cosmetic formatting affects the overall appearance of the view and enables you to change the default green bar color. Figure 3-6 shows a pivot table on a dashboard page with green bar styling.

Figure 3-6 Pivot Table with Green Bar Styling

To add green bar styling and cosmetic formatting to a table or pivot table:

1. On the toolbar of the editor, click the View Properties button or from the "Compound Layout" in the Results tab, click the View Properties button.

   The "Table Properties dialog" or "Pivot Table Properties dialog" is displayed.

2. To add green bar styling, click the Enable alternate styling box.

   To change the way the styling is applied, select a style from the list.

3. To add cosmetic formatting, click the alternate formatting button.

   The "Edit Format dialog" is displayed.

4. To change the default green bar color, choose a new background color for the cell format. Make any other appropriate changes, and click OK.

5. In the Properties dialog, make any other appropriate changes, and click OK.

   For more information about cosmetic formatting, see "What is Cosmetic Formatting?"

Formatting the Visual Appearance of Graphs

You can format the visual appearance of graphs based on two settings:

• The position of the graph elements (such as lines or bars in a line-bar graph or slices in a pie graph).

  See "Graph Formatting Based on Position."

• Conditions applied to columns. See "Graph Formatting Based on Columns."

Graph Formatting Based on Position

Positional formatting enables you to customize the appearance of a graph based on the position of graph elements; that is, the numeric sequence in which graph elements (for example, bars) are displayed in a group. A group is determined by the attribute columns that are displayed in the Group By drop target area. (For information on drop target areas, see "Understanding Drop Targets.")

For example, suppose that you have a bar graph whose criteria include the C50 Region, 1 - Revenue, and 2 - Billed Quantity columns. 1 - Revenue is displayed first, then 2 - Billed Quantity in the Measures drop target area. C50 Region is displayed in the Group By drop target. In this graph, 1 - Revenue is in position 1 and 2 - Billed Quantity is in position 2 for each regional grouping as shown in Figure 3-8.

Figure 3-8 Example of Position in a Graph

You can format the visual appearance of a graph based on position in terms of its color, line width, and line symbols.

Note: Positional formatting is not supported for waterfall graphs.

What Terms are Used with Trellis Views?

Table 3-8 defines the terms that are used with trellis views.

What Makes a Trellis View Unique?

The trellis view, also referred to as a trellis graph, is the same as a pivot table—with one major exception: the data cells within the trellis contain graphs. Whereas a stand-alone graph type such as a single bar graph or a single scatter graph works on its own, the trellis graph works only by displaying a grid of nested graphs, known as inner graphs. So a bar-graph trellis view is actually comprised of multiple bar graphs.

In a general sense within the field of business analytics, a visualization is a visual representation of data, displayed in graphs, gauges, maps, and so on. In the trellis editor, within the Layout pane, there is a drop target called Visualizations; this is where you drag the columns for the inner graphs that will comprise the trellis you are building.

The visualizations that make up a simple trellis view are all graphs, and they can be many types of the existing stand-alone graphs described in "What Types of Graphs Are Available?" The visualizations that make up an advanced trellis are always microcharts, of the graph subtypes Spark Line, Spark Bar, or Spark Area. Ideally, the microcharts within an advanced trellis are placed alongside numbers (representing the same measure). For more information, see "What Are Microcharts?"

What Are the Functions of Trellis Views?

For the most part, a trellis view behaves like a pivot table, and the main difference between a trellis and a pivot table is the way the data cells appear.

In the row and column label cells of a trellis, you can:

• Right-click to move measure labels

• Right-click to sort data

• Drag to reposition rows and columns

In the data cells of a trellis, you can hover the mouse pointer to show related contextual information.

Numeric data cells in a trellis behave the same as numeric data cells in a pivot table.

The ways in which the behavior of a trellis view differs from the behavior of a pivot table are the following:

• Graph data cells: There is no right-click functionality for the data cells in simple trellises, nor drilling in trellis graph data cells (left-click functionality).

• Microchart data cells: When you hover the cursor over the data cells in spark graphs, you are shown contextual information (such as first, last, minimum, and maximum values) that otherwise is not displayed as it would be in a pivot table view.

  Figure 3-10 shows an advanced trellis twice, the second time with a tooltip displayed as the cursor hovers over a microchart data cell. Microcharts do not show axis labels, as regular charts do, so it is not immediately obvious what the inner graph dimensionality is. Use a microchart's tooltips to understand the data being represented inside the graph—sample individual values, as well as the overall dimensionality.

Figure 3-10 Sample Microchart Shown Before and After Mouse Hover for Tooltip

What Are Microcharts?

A microchart is, as its name implies, a tiny chart. A microchart is displayed in trellis views of the Advanced Trellis subtype. A microchart is unique as a graph type in that it can never be an independent, stand-alone graph. It can be used only within the context of a trellis view, and its meaning comes only from the fact that it is one of many small multiples.

Spark Graphs in Oracle BI EE

A microchart can be one of several graph subtypes, including Spark Line, Spark Bar, and Spark Area.

Figure 3-11 shows a sample trellis composed of the Spark Line subtype, and numbers.

Figure 3-11 Sample Microchart in a Trellis View

Spark graphs, also called sparks, are unique from line graphs, bar graphs, and the other stand-alone graphs available in Oracle BI EE. Spark graphs are embedded mini-graphs that illustrate a single trend. Simple in their appearance, they do not include axes or labels and they get their context from the content that surrounds them. Each type of spark graph has only one measure, which is hidden; the scale is relative to itself only.

In Oracle BI EE, the visual appearance of sparks emphasizes trends, and within those trends, the highest and lowest values. Due to the condensed manner in which sparks display trends, it is possible for many trends to be compared (along with numeric values) on a single page.

Notice how the advanced trellis in Figure 3-11 visualizes the same measure twice (1 - Revenue), setting the first instance to "Number," and associating a time dimension (T02 Per Name Month) with the second instance (1 - Revenue renamed to Revenue Trend), while displaying the second instance as a spark. This advanced trellis shows the total value for the year, and next to it, how the total value trended over the year.

While sparks are useful for certain types of analysis, such as high-level observation of trends and spotting of patterns, it is important to note that they do not illustrate the same specificity as their larger, fuller-featured counterparts.

Working with Spark Graphs

Sparks are unique mainly because they are small and because they can display a lot of information in a very constricted space. In Oracle BI EE, a spark graph is also different from a stand-alone graph in that, as a microchart, it can only be used within trellis views.

You can modify the size of your sparks in the same way that you do with full-featured graphs, in the Graph Properties dialog.

Figure 3-12 shows a sample of a spark graph with markers for highest and lowest values in revenue data over the course of a year, for three years.

Figure 3-12 Sample of a Spark Graph

For more information about creating trellis views that include sparks, see "Design Considerations for Trellis Views and Microcharts."

About Simple Trellis Versus Advanced Trellis

When you create a trellis view, the first thing you do is choose between two subtypes: Simple Trellis and Advanced Trellis. The Simple Trellis subtype displays a single type of inner visualization, for example, all bar graphs. The inner visualization always uses a common axis, so that all inner graphs are viewed on the same scale. (This concept of a common axis is also referred to as a synchronized scale.) Having a common axis makes all graph markers easy to compare across rows and columns.

The Advanced Trellis subtype allows for display of multiple visualization types within its grid. An advanced trellis illustrating sales trends might show a grid containing numbers in the cells of one column (revenue, for example), while another column alongside the numbers column displays Spark Line graphs in its cells, and those Spark Line graphs visualize the same measure as represented by the numbers (again revenue, but over a time period). Next to that column, a different microchart might be displayed, such as a column of Spark Bar graphs that visualize a different measure, such as unit totals.

Each measure that is visualized is assigned a different inner graph type. Each cell of the grid is scaled independently.

Think of an advanced trellis as a pivot table with spark graphs inside its data cells. But, for each measure you add, you can optionally associate a dimension and render it as a microchart visualization. This makes an advanced trellis very different from a simple trellis. In a simple trellis, all of the measures are rendered in the same visualization, along with additional dimensions.

Design Considerations for Trellis Views and Microcharts

The following are some ideas to consider when designing content displayed in trellis views:

• For comparisons, choose the Simple Trellis subtype.

• For trend analysis, choose the Advanced Trellis subtype.

• The inner graphs that make up a trellis should be readable and not too dense, so a trellis view is not especially useful for displaying multiple series or multiple groups. If you cannot easily target a data point with your mouse (to be shown a tooltip), then it is likely that the inner graph is too dense to be readable.

• When using the Simple Trellis subtype, note the following:

  • Designing a simple trellis is like designing a pivot table, except that the total number of cells that can be rendered is much less for a trellis.

  • The main difference between designing a simple trellis and designing a pivot table is that for a trellis, one or two of the dimensions can be associated with the visualization; so, that many less dimensions must be added to the outer edge.

  • It is best to design the trellis with a small number of outer-edge dimensions. The entire graph series should be visible at once (for easy comparison of like to like) with no need to scroll. If you must show additional dimensionality, consider adding the dimensions to the graph prompt.

  • When determining which data to show in column headers and which to show in row headers, the column headers should show one or two dimensions (each dimension with a small number of members). Most often, the dimension shown in column headers is time. Place the remaining dimensions in the row headers or in graph prompts.

• When using the Advanced Trellis subtype, note the following:

  • The key use case for an advanced trellis is to show trend graphs alongside numeric values, in a compressed form. So a typical advanced trellis contains a combination of spark graphs alongside number representations of the same measure.

  • Ideally, place no dimensions in the column headers, just place the measures here.

  • The dimensionality typically associated with a spark graph is time. As there are no visible labels in a spark graph, it is important that the data visualized is intrinsically ordered. For example, a spark graph visualizing regions would be meaningless, because the ordering of the regions (which would be the specific bars, in a Spark Bar graph) is not intuitive.

  • Just as when designing pivot tables, you generally display time on the horizontal axis, with the other dimensions displayed on the vertical axis. The eye then scans from left to right to see how the dimensionality changes over time.

Using Auto Correct

A map view error can occur for various reasons. If the issue appears to be related to missing layers, maps, or styles, then it might be possible to correct the map by replacing the missing map view components with similar items that exist in the spatial metadata. Before contacting your administrator, you can attempt to correct the issue yourself. To do so, perform these steps:

1. Edit the map in the Compound Layout. A View Error message box displays.

2. Click Yes in the View Error message box and the Map View compiler will attempt to auto correct the error. If you click No, you can use the Auto Correct icon at a later time to attempt to fix the error. If the compiler can correct the error, the map displays.

3. Sometimes only a partial correction may be possible. If this is the case, a Partial Fix dialog displays and provides a visual cue regarding the layers that must be deleted to proceed with auto correction. Click Yes to proceed. Although some formats may be deleted, the majority of the original map's formats are preserved.

What are the Functions of Map Views?

Map views offer the following functions:

• You can display multiple attribute columns and measure columns on a map view. Map views do not support hierarchical columns.

• You can format a map view, including with colors, bar graphs, pie graphs, variably sized bubbles, images, lines, or colored shapes that provide the ability for binning and other formatting options.

• You can drill in information windows. When you hover over a value, you see a popup with information, such as the geographic region (city, state, or country), the measures in the form of column names and column values and formatting metrics, and non-geographic data such as year. The appropriate related data is highlighted in the interactive pane as well. You can click the value to display the actionable links for drilling in the information window, then click the appropriate link.

What Terms Are Used with Map Views?

Table 3-9 defines the terms that are used with map views.

What Are the Components of Map Views?

A map view contains the following components:

• Main content — The main content is the background or template map, which provides the background geographic data and zoom levels. The main content can be any image that can be configured using MapViewer, for example, the floor maps of office buildings and the appearance and presence of items such as countries, cities, and roads.

• Layers — One or more interactive or custom layers overlay the main content. For information, see "What Are Layers?"

• Toolbar — Provides buttons that allow you to manipulate map contents directly. The map view itself has a toolbar. The content designer specifies whether to display the toolbar for the map view on a dashboard page. On a dashboard page, the toolbar is displayed directly over the map and contains only the Pan, Zoom Out, and Zoom In buttons. The toolbar is visible by default and its display is controlled by the "Map Properties dialog: Tools tab."

  Each button represents a mutually exclusive mode for manipulating the map contents. The default mode is Pan. When you click a button to activate a mode, that button becomes highlighted and the mouse pointer changes to match the image on the button.

  The toolbar in the Map editor contains additional options for modifying the map view.

• Zoom controls — Adjusts the detail of the geographic data that is shown in the map view. For example, zooming in from a country might show state and city details.

  On the Administration page, the administrator specifies which zoom levels each layer is visible for. You can have multiple zoom levels for one layer, and you can have a single zoom level associated with multiple layers. When you zoom, you change the map information at that zoom level, but you do not affect the display of Oracle BI data at that level. You affect the display of Oracle BI data by drilling.

  The zoom controls consists of pan buttons and a zoom slider that render in the upper left-hand corner of the map view. When the zoom control is zoomed-out all the way, the zoom level is set to 0 and the entire map view is displayed.

  The "Map Properties dialog: Tools tab" lets you determine the visibility of the zoom control. By default, the map is initially zoomed into the highest zoom level that fits the entire contents of the top-most layer. For example, if the highest ordered layer contains data only in the state of California, then the map zooms to the highest zoom level that still shows all of California.

  • Pan buttons — Consists of buttons (with arrows that point north, south, east, west, northeast, northwest, southeast, and southwest) at the top of the zoom control. You can use these buttons to move the entire map in specific directions. When you click the pan center button, the map returns to the zoom level and the center that the map was displayed with initially.

  • Zoom slider — Consists of a slider with a thumb for large scale zooming and buttons for zooming a single level. You can use the plus button to zoom in and the minus button to zoom out one level at a time. When the thumb is at the bottom of the slider, the zoom level is zero.

• Scale tool — Also known as Distance Indicator. Provides a key to distance interpretation of the map and consists of two horizontal bars that display in the lower left-hand corner of the map view below the information panel and above the copyright. The top bar represents miles (mi) and the bottom bar represents kilometers (km). Labels are displayed above the miles bar and below the kilometers bar in the format: [distance] [unit of measure]. The length and distance values of the bars change as the zoom level changes and as the map is panned.

• Legend — The legend is a semi-transparent area in the upper right-hand corner of the map view that you can display and hide. The legend shows the information that relates to the current zoom level. The legend provides a read-only visual key for symbols, layers, and formatting on the map and displays the following:

  • All visible formats that are applied to the map. If a format is turned off, then the corresponding legend item is hidden also. If a format is turned on but zoomed out of view, then it is not displayed in the legend. The legend displays text such as "No formats defined for current zoom level" if you have no formats defined at the zoom level that is currently displayed.

  • Scrollbars, if needed.

  Selecting a format on the map will cause the corresponding legend item to be highlighted. Highlights have varying granularity, depending on the selected formats (for example, a pie graph does not have the level of granularity that color fill has). See "How Do Formats Affect Layers?"for additional information.

  Use the Expand Map Legend and Collapse Map Legend buttons in the upper right-hand corner to control the display of the legend.

• Overview map — Consists of a miniature view of the main map that is shown in the lower right-hand corner of the main map. This overview map provides regional context and lets you change the viewable area of the main map without having to use the pan buttons.

  The following items are part of the overview map:

  • Reticule: Displays as a small window that you can move across a miniature view of the main map. The position of the reticule in the miniature map determines the viewable area of the main map. As you move the reticule, the main map is updated automatically. You can also pan in the overview map without using the reticule.

    The overview map is automatically hidden if the reticule cannot be shown. This hiding generally happens when the scale difference between successive zoom levels is too small to show the miniature view in the overview map.

  • Show/Hide button: Displays in the upper left-hand corner when the overview map is displayed. When you click the Show/Hide button, the overview map becomes invisible and only the button can be seen in the lower right-hand corner of the main map.

• Interactive panel — Accompanies the view in a dashboard and in the "Compound Layout." The top section of the interactive panel enables you to create and edit BI data formats in the Analysis editor. If a format has editable thresholds, then a slider is displayed in the Map editor that enables you to edit thresholds by dragging the slider. The interactive panel enables you to rearrange formats within a geographic layer. For example, if the States layer has three formats, then you can select the order in which the formats are displayed.

  When displaying a tooltip by hovering your mouse cursor over a map area, the corresponding detail is updated and highlighted in the interactive panel.

  Dashboard users can control the visibility of formats (by turning them on or off) and can adjust format thresholds if the content designer has allowed them to.

  The lower section of the panel includes the Feature Layer area, where you can select non-BI layers to add to the map. A non-BI layer is one that has not been associated with a BI column. Typical examples include Google Maps™ Tile Layer and Bing Maps™ Tile Layer, highways, parks, or automated teller machines. You cannot apply formats to non-BI layers.

What Are Layers?

Layers are collections of geometries that share common attributes. Layers can be either predefined or custom:

• A predefined layer is one whose geometry is defined in a spatial table in an Oracle Database. The administrator makes predefined layers available using the Administration pages, as described in "Administering Maps" in System Administrator's Guide for Oracle Business Intelligence Enterprise Edition.

• A custom point layer is one that you define while editing a map view, as described in this section.

Layers can be of different types. A polygon layer represents regions, such as states. An example is a New England layer for the United States that consists of Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, and Vermont.

A point layer represents specific points on a map, based on a coordinate system. For example, a point layer might identify the locations of warehouses on a map. The layer can use a different image for the type of inventory (electronics, housewares, garden supplies) in a set of warehouses to differentiate them from each other.

You can create a custom point layer that applies points to a map using longitude and latitude coordinates. For example, suppose that your company is headquartered in New York City. You can create a custom point layer that displays your company icon over New York City, and that icon is always displayed whenever a map that includes New York City is shown. The custom point layer is always on top of the other layers and is not affected by zoom levels. The custom point layer is used only by the current map view in the current analysis; it is not used by other map views, even for the same analysis.

You can select layers to be visible or hidden on a map, but you cannot modify predefined layers. You also create formats to apply to the layers, such as colored regions, bubbles, points, lines, or bar or pie graphs. Not all formats are available for all layer types. For example, point layers cannot have color fill formats.

Creating Map Views

When the administrator has configured maps, you as the content designer can create analyses whose data is displayed in map views.

You create a map view after selecting columns to display in that view. If the administrator has specified multiple background maps, then the map view is initially displayed using the first background map that was specified by the administrator that includes at least one layer that has been associated with a column that you selected. When editing the map view, you can select a different background map. You can apply layers to the background map and formats to the layers.

To create a map view for an analysis:

1. Create an analysis by selecting the attribute and measure columns to display on a map view. You generally select attribute columns that are related to geography, such as Cities, States, or Regions.

   Select only those geography columns that the administrator has mapped to layers using the Administration pages, as described in "Administering Maps" in System Administrator's Guide for Oracle Business Intelligence Enterprise Edition.

2. Select the Results tab.

3. On the toolbar, click the New View button, then select Map.

   If you see a message that states that a background map is required to render a map, then no metadata exists to populate the map. Contact the administrator about configuring the metadata for maps using the Administration page.

   Otherwise you see a map that uses the background map that was specified on the Administration page.

4. Click the Edit View button to display the view in the "Results tab: Map editor."

   You see a default map view in which the measures have been divided into reasonable bins and color coding has been applied. You can adjust the map view and layers as you like. If you do not see any default format created, then you must create a format.

5. Specify map view properties, such as canvas size or master-detail linking by using the "Map Properties dialog."

6. Apply formats to the layers, as described in "Applying Formats to Layers."

How Do Formats Affect Layers?

A map view uses columns of Oracle BI EE data. Each column has a set of properties that define its characteristics, such as for formatting and interaction. Any formatting that has been applied to a column is not applied to the map, except for the settings for interaction. Any formatting that originates from thresholds that the map contains is applied.

You can apply various kinds of formats to map views. The following list describes the options for defining formats to apply to BI layers. You cannot apply formats to non-BI layers.

• Color Fill — Displays the "Color Fill (Layer) dialog," which you use to render areas in fill colors that indicate that an area meets a particular condition.

  Color fill formats apply to regions or polygons. For example, a color fill format might identify a range of colors to represent the population in the states of a region or the popularity of a product in the states of a region. A map view can have multiple color formats visible at different zoom levels. For example, a color fill format for the layer at zoom levels 1-5 might represent the population of a state, and the county median income for the layer at zoom levels 6-10. You can also specify different colors to identify a range of data values.

• Bar Graph — Displays the "Bar Graph (Layer) dialog," which you use to render a series of data as a bar graph within an area. Graph formats can show statistics related to a given region such as states or counties. For example, a graph format can display the sales values for several products in a state.

  Even though you can create multiple graph formats for a particular layer, such creation is not recommend as the formats might overlap on the layer and the displayed results might be undesirable.

• Pie Graph — Displays the "Pie Graph (Layer) dialog," which you use to render a series of data as a pie graph within an area.

• Shape — Displays the "Variable Shape (Layer) dialog," which you use to render a measure column that is associated with an area by drawing markers or shapes within the region. You can also specify different colors for the shape to identify a range of data values.

• Bubble — Displays the "Bubble (Layer) dialog," which you use to render a bubble within an area, similar to the shape format.

• Image — Displays the "Image (Layer) dialog," which you use to render an image within an area, similar to the shape format. You can specify different images to identify a range of data values. You select images that have been specified by the administrator.

• Line — Displays the "Line (Layer) dialog," which you use to render a line on a map.

  You can include lines on maps to display paths such as highways, railway lines, and shipping routes. You can specify the width of lines and you can use the Map Wrap-Around feature on the "Map Properties dialog: Canvas tab" to allow lines to be unbroken, such as when showing an airline flight path from San Francisco to Tokyo.

  You can vary the width of a line by each measure to accentuate a feature.

• Custom Point — Displays the Format Custom Point (Layer) dialog, which you use to render a point format, such as a bubble, image, or shape in a layer. Custom points are displayed at all zoom levels and on top of all other map formatting. When you create a Custom Point format, you select columns to specify the latitude and longitude.

Applying Formats to Layers

To apply a format to each layer as appropriate, use one of the following ways:

• Click the Create a new Map Format link, if no layers are specified in the Map Formats list.

• Click the Add New Map Formats button, either in the Map Formats title bar or beside a layer name.

For more information, see "Showing or Hiding Formats on a Map View."

Setting the Initial View Ports for Map Views

You can use options on the "Map Properties dialog: Interaction tab" to specify the view port (the initial center of the map and zoom level) when a map view is first loaded or refreshed in a browser. This specification allows you to affect the initial display of the map for users.

Editing Map Views and Displaying Map Views on Dashboard Pages

Many of the same functions are available for map views, whether you are editing them or displaying them on a dashboard page. Some functions are available only when editing map views, as described in the following list:

• When you edit a map view and work with layers, you create formats for the BI layers. You can display a dialog for adding and editing formats. You can also specify the order of formats for each layer. The order affects the visibility of the formats for the layer. Formats that are displayed higher in the list overlay formats that are lower in the list. When you display a map view, you can turn on and off the display of formats, but you cannot add or remove them from the map view.

  As the content designer editing a map view, you can control the display of layers, but only of those layers that the administrator has associated with this background map. The administrator must ensure that BI layers are ordered higher than non-BI layers. If a non-BI layer is ordered higher than any BI layers, then the non-BI layer is displayed on top of the lower BI layers on the map, which prevents the BI layers from being interactive.

• When you edit a map view, you decide whether users of dashboard pages can modify the following the thresholds of Color Fill formats using sliders. When you display a map view, you can modify the thresholds of Color Fill formats (if that ability was provided). If you close and re-open the map view, then you see the thresholds or scaled lines at the same state in which you left them. To save the thresholds when you leave the dashboard, first save the customizations of the dashboard.

• When you edit or display a map view, legend contents display all active and visible formats.

For more information on the functions that are available when you display a map, see "Working with Map Views on Dashboard Pages."

Understanding Treemap Views

By default, the first measure of the analysis in the Criteria tab is selected as the Size By measure, and the second measure is selected as the Color By measure. If there is only one measure in the analysis, this measure is the default for both Size By and Color By options. Additionally, the Style element defaults to Percentile Binning with "quartile" as the value for the number of bins. See the "Treemap Properties dialog" for additional information.

Treemaps have the following characteristics:

• Colored tiles are formed by the grouping and intersection of the columns placed in the Prompts, Sections, Group By, Size By, and Color By drop targets. See "Additional Components Common to Treemap Views" and "Drop Target Guidelines for Treemaps" for additional information.

• Levels of data are displayed within a predefined, rectangular-shaped, confined space for two measures.

• Attribute and hierarchical columns are supported. Skip-level hierarchies are not supported in the Group By area of treemap.

• Tiles are displayed as percentile bins or as a continuous color. See "Additional Components Common to Treemap Views" for additional information.

• A legend (that can be hidden) displays below the treemap and contains:

  • Two measures (those selected in the Size By and Color By lists) and their corresponding labels.

  • Number of specified bins (for example, quartile), color coded and labeled, or a gradient bar that is displayed as a continuous color fill and is labeled "low" to "high."

• First Group By dimension is displayed as the group (header) label.

• The order of the Group By dimensions implies the nesting order within the treemap. The last dimension in the Group By is the lowest level and this dimension name is displayed as the tile label. If the label is too long to fit on the tile, it is truncated. Full values for the labels display in the tooltip.

• A "transparent" diagonal pattern of stripes is displayed for null values.

• This is available in read-only mode on mobile devices.

The Treemap editor is composed of three panes or areas available for you to use in customizing the treemap view. These three panes are arranged vertically (differentiated from tables, pivot tables, and so on that are arranged horizontally). These panes include:

• Layout pane — Controls the columns that display as tiles, sections, prompts, and groupings, as well as the formatting for labels and measures. See "Drop Target Guidelines for Treemaps" and "Additional Components Common to Treemap Views" for additional information.

• Treemap Results pane — Displays the results of the treemap view and immediately reflects any customizations.

• Selection Steps pane — Displays the selection steps in effect for the analysis and treemap. See "Working with Selections of Data" for additional information.

Working with Treemap Views

You can:

• Left-click to drill on the tile or on a group. When drilling in multiple-level hierarchies, all members from the lowest levels display as tiles, and the detail level data replaces the current data. For example, when you drill down on a country name, such as United States, the treemap displays data for the state (or provinces) in that country, but not for the country itself.

• Right-click to display a context menu of actions, such as Drill, invoke actions, Keep Only, Remove, or focus on a specific tile. See "Right-Click Interactions in Views" for additional information.

• Hover the cursor over the group or tile to display a tooltip. The tooltip for the group displays the aggregated measure values at that intersection, the header label, and header value. The tooltip for a tile displays the tile member and the Size By and Color By labels and values.

• Drag and drop an analysis containing a treemap view on to a dashboard (see "Adding Content to Dashboards" for additional information). Once added to a dashboard, you can:

  • Print to a PDF

  • Print to HTML

  • Export to Excel

  • Export to PowerPoint

• Navigate using treemap breadcrumbs. Treemap breadcrumbs are displayed above the treemap view. Use treemap breadcrumbs to traverse back to the original view and to previous levels in the tree. Treemap breadcrumbs:

  • Reflect the contextual drill path

  • Return you to the original view, and remove all the contextual drills when you click the up arrow icon. This is the page-level treemap breadcrumb or "home" (up arrow).

  • Remove the contextual drills associated with the specific item when clicking a link that is not the "home" link.

• Edit a treemap view to change the measures, properties, and so on.

To edit a treemap view:

1. Display the "Results tab: Treemap editor." For information, see "Editing Views."

2. To customize or set the properties of a treemap, click the Treemap Properties button on the toolbar. The "Treemap Properties dialog" is displayed, where you can set properties:

   • Related to the size of the treemap (see "Treemap Properties dialog: General tab")

   • To control the appearance of the tile, such as the background and border colors for the legend and groups (see "Treemap Properties dialog: Style tab")

   • Show or hide the legend (see "Treemap Properties dialog: General tab")

3. Use the buttons on the toolbar of the editor to perform functions, such as printing or exporting a view (see "Toolbar Buttons Common to All Views") or use a context menu to perform similar functions (see "Right-Click Interactions in Views").

4. In the Layout pane, select the Percentile Binning or Continuous Color Fill options to change the color palette of the view. See "Additional Components Common to Treemap Views" for more detailed information.

   Change the measures and attribute and hierarchal (excluding skip-level) columns to visualize your new data in more meaningful ways by using Group By, Size By, and Color By options.

   See "Treemap Properties dialog" for additional information on tile attributes.

5. Right-click to perform basic view interactions. For information, see "Right-Click Interactions in Views."

Understanding Drop Targets

In the Layout pane, the columns in a data view are displayed in drop targets. Drop targets indicate where a column can be inserted, moved to, or dropped. They represent a valid position for a column.

You use drop targets to modify the way data is arranged in a data view by dragging and dropping columns to different targets within the view.

A data view can contain one or more of the following drop targets, depending on the type of view:

• <view-type> Prompts — Provides an interactive result set that enables users to select the data that they want to view. The values from the columns that are displayed in this drop target are used as the initial criteria. In a view, these values are displayed in a drop-down list for selection, which is often referred to as the "page edge."

• Sections — Populates the areas that divide the view into sections. If you select the Display as Slider option in this drop target, then the values of the columns that are dropped in the Sections drop target are displayed as a section slider rather than as unique views.

• <view-type> area — Simulates the plot area or the body of the view itself and assists you in seeing what the view looks like.

  For tables, this area contains the Columns and Measures drop target, which contains all the columns in the view. In tables, all measures are treated as columns.

  For all other data views, this area contains the following drop targets:

  • Measures drop target — Populates the part of a view that contains summary data. Depending on the type of view, this area might include a single Measures drop target (for example, for pivot tables) or might contain sub-drop targets (for example, the Bars (Y1-Axis) and the Lines (Y2-Axis) for line-bar graphs). You drag and drop measure columns to these drop targets.

  • Other drop targets — Used to summarize the columns in the measure drop target or targets. You generally drag and drop attribute and hierarchical columns to these drop targets.

    The other drop targets that are displayed in a view depend on the type of view as described in Table 3-10.

  Table 3-10 Other Drop Targets in Data Views

  View	Drop Target or Targets
  Pivot table	Includes these drop targets: Columns — Shows a column in a column orientation. Pivot tables can contain multiple columns. Rows — Shows a column in a row orientation. Pivot tables can contain multiple rows.
  Gauge	Rows — Shows the columns that are displayed in the gauges.
  Bar, line, area, line-bar, time series line, pareto, scatter, or bubble graph	Includes these sub-drop targets within the main drop target (Bars, Line, Area, Bars & Lines, Line, Points or Bubbles). Target names differ depending on graph type. For example, Group By is Bubbles for bubble graphs and Points for scatter graphs. Group By — Clusters the axis labels into groups. For example in a vertical bar graph whose criteria includes the Region, District, and Dollars column, if this drop target contains the Regions column, then the data is grouped by region on the horizontal axis. Vary Color By — (Not enabled for pareto.) Shows each column value or column value combination in a different color.
  Radar graph	Radar Sections — Shows column values as points on each line along a radius of the circle.
  Pie graph	Includes these drop targets: Pies — Shows each column value or column value combination as a separate pie. Slices — Shows each column value or column value combination as a separate slice of the pie.
  Waterfall graph	Includes this drop target: Group By — Clusters the axis labels into groups. Attribute and hierarchical columns are placed in the Group By area. If you are using a measure hierarchy, a generic measure column is placed in the Bars drop target and the measure dimension is placed in the Group By drop target. (Measure hierarchies apply to Essbase data sources.) See Metadata Repository Builder's Guide for Oracle Business Intelligence Enterprise Edition for additional information on measure dimensions and measure hierarchies.
  Funnel graph	Stage — Shows each column value as a stage in the funnel.
  Trellis	Includes these drop targets: Columns — Shows a column in a column orientation. Trellises can contain multiple columns. Rows — Shows a column in a row orientation. Trellises can contain multiple rows. Includes these sub-drop targets within the main drop target Visualization for simple trellis views: Group By — Clusters the measures into groups. Color By — Shows each measure in a different color, for example, in a vertical bar graph of a trellis, all the bars for Revenue are blue while the bars showing Billed Quantity are red. In a Scatter graph, use this drop target to vary the points by color. In a Bubble graph, use this drop target to vary the bubbles by color. Bar Axis — In a Line-Bar graph comparing revenue and billed quantity by region, shows one of two measures, such as Revenue. Line Axis — In a Line-Bar graph comparing revenue and billed quantity by region, shows one of two measures, such as Billed Quantity. Pies — In a Pie graph, adding a dimension here creates multiple pies. Slices — In a Pie graph, shows measures as slices of varying colors within pies. Points — In a Scatter graph, shows dimensions as points. Each dimension member is shown as one point. Horizontal Axis — The measure values control the horizontal position of the members. In a Scatter graph, you can drop one measure in this target. In a Bubble graph, each measure in this drop target is shown as one bubble. Vertical Axis — In a Scatter graph, shows one of two measures, such as a point. In a Bubble graph, shows one of three measures as a bubble. Bubbles — In a Bubbles graph, shows measures as bubbles of varying size. Size — In a Bubble graph, shows one of three measures as the size of a bubble. Includes these sub-drop targets within the main drop target Visualization for advanced trellis views: Areas — In a Spark Area microchart, shows columns displayed as areas. Bars — In a Spark Bar microchart, shows columns displayed as bars. Lines — In a Spark Line microchart, shows columns displayed as lines.
  Performance Tile	Includes this drop target: Measure — Shows the specific value of the column that displays on the tile. See "Drop Target Guidelines for Performance Tiles" for additional information.
  Treemap	Includes these drop targets: Group By — Represents the top level of hierarchical data that is sliced to produce or describe a container of aggregated values. The aggregated values display as rectangular tiles. Size By — Represents the distribution of the tiles within their parent. The size of the children are always equal to the size of their parent. Color By — Represents a distribution of values across all of the tiles at the same level.

  
  

• Excluded — Excludes columns from the view results but leaves the columns as part of the analysis. See "Columns in the Excluded Drop Target" for more information.

In addition, each <view-type> area, except for the Table area, the Waterfall Graph area, Pareto Graph area, Treemap area, and the Trellis (Simple) area, contains the Measure Labels element. The Measure Labels element represents the labels for all the Measures columns in the drop targets in the Measures area. You can modify how measure labels are shown in a view by dragging it from one drop target and dropping it in another. For example, in a vertical bar graph, you can show each measure label in a different color by dragging and dropping the Measure Labels element to the Vary Color By drop target.

In pivot tables, you can also edit the format of measure labels or hide them.

Region    City    Dollars
East       NY     1000
East      Boston   500

East    1500

East    1000
East     500

Adding and Rearranging Columns in Views

Using the view editor and the Layout pane, you can easily modify and change the order of columns in the following ways:

• Drag and drop columns in tables and pivot tables to the desired positions in the editor using the handles and drop targets. For example, if you have two columns in the Rows section of a pivot table, reverse the order of the columns by dragging and dropping the first column after the second one. In a table, you can drag and drop columns, but you cannot stack columns, as you can in a pivot table.

  You can also drag and drop columns in this way in the Compound Layout.

  
  

  Note: If you have deselected Move Columns in the "Analysis Properties dialog: Interactions tab," you cannot move a column in a view at runtime.

  
  

• Drag and drop columns in the Layout pane. A target is active and ready for the "drop" when it appears highlighted. When you hover the mouse pointer over a column in the Layout pane, the cursor state changes from the pointer to a move cursor when you can "grab" the column and move it over a drop target. For example, you can easily move a column in a pivot table from the Rows drop target to the Sections target to create a unique pivot table for each value in the column. For details of dragging and dropping columns in the Layout pane of the trellis editor, see "Drop Target Guidelines for Trellises."

  For details of dragging and dropping columns in the Layout pane of the Treemap editor, see "Drop Target Guidelines for Treemaps."

  For more information on drop targets, see the "Layout pane."

• Add a column to a graph or gauge. To do so, drag the column from the Subject Areas tab to the appropriate location in the view editor or to a drop target in the Layout pane.

• Remove columns in the Layout pane. For example, you can easily remove a column in a view by selecting Remove Column from the More Options button. Removing columns differs from excluding columns, which is described in "Understanding Drop Targets."

This list provides only a partial summary of where dragging and dropping can occur. You can drag and drop columns and catalog objects whenever you see the "Subject Areas pane" and "Catalog pane." You can also drag and drop items in views on dashboards. See "Columns in the Excluded Drop Target" for more information.

Setting Properties for View Bodies and Drop Targets

In the Layout pane, you can click the Properties button to display a dialog in which you specify properties for the view body (such as Pivot Table) or for a drop target (such as Sections). For example, you can specify whether to display headings, set background color, and insert page breaks.

To modify view body or drop target properties:

1. In the view editor, display the Layout pane and click the Properties button beside the view body (for tables and pivot tables) or drop target name.

   The Properties dialog for the view body or drop target is displayed.

2. Complete the appropriate fields and click OK.

Displaying Running Sums and Relative Values for Measure Columns in Pivot Tables

You can use the Layout pane to display running sums or the relative value of measure columns in pivot tables, as described in the following sections.

Defining Section Sliders in Graphs, Gauges, and Funnels

A section slider displays members of one or more attribute or hierarchical columns as values on a rectangular bar and provides mechanisms to select a value. You use a section slider to limit the data that is shown in a graph, gauge or funnel.

Figure 3-23 shows an example of a section slider. It displays the members of the Product Type column. Using this slider, for example, you can limit the data that is shown in a graph, gauge, or funnel to a particular product type, such as Cell Phones.

Figure 3-23 Example of a Section Slider

A section slider consists of the following components:

• Slider bar — Displays the members of one or more attribute or hierarchical columns as values along a rectangular bar.

  
  

  Note: The administrator configures the maximum number of values that can be displayed on the slider bar. However, you can set a maximum lower than the system maximum by setting the Maximum number of section slider values field in the "Section Properties dialog."

  
  

• Slider thumb — Indicates the current value of the section slider. The thumb in Figure 3-23 indicates that the current value is Cell Phones. You can drag the thumb to the desired value.

• Decrease button — Moves the slider thumb to the value to the left of the current value. For example, in Figure 3-23, clicking the Decrease button (the second button from the left on the slider) moves the slider thumb to the value Camera.

• Increase button — Moves the slider thumb to the right of the current value. For example, in Figure 3-23, clicking the Increase button (the right-most button on the slider) moves the slider thumb to the value Fixed.

• Play button — Sequentially moves the thumb through the slider values. For example, in Figure 3-23, clicking the Play button (the left-most button on the slider) moves the slider thumb to the value Fixed and then to Install, and so on. After being clicked, the Play button changes to a Pause button to allow you to stop on a particular value.

As the thumb moves through the slider values, the minimum and maximum values of the axes are based on data across all slider sections and remain the same. The exception to this is in pareto graphs, where the axes are plotted from 0% to 100%.

To define a section slider in a graph, gauge, or funnel:

1. Open the analysis that contains the graph. gauge, or funnel in which you want to define a section slider.

2. Click the "Analysis editor: Results tab."

3. Click the Edit View toolbar button in the graph, gauge, or funnel view.

   The "Results tab: Graph editor,", "Results tab: Gauge editor", or "Results tab: Funnel editor," is displayed.

4. For each column to be displayed on the section slider, in the "Layout pane" of the Graph, Gauge, or Funnel editor, drag and drop the column to the Sections drop target.

5. Select Display as Slider.

6. Click Done to close the editor and return to the Results tab.

7. Click the Save Analysis toolbar button to save your changes.