Filters are used to limit the results that are displayed when an analysis is run, so that the results answer a particular question. Based on the filters, only those results are shown that matches the criteria passed in the filter condition.

Filters are applied directly to attribute and measure columns. Filters are applied before the query is aggregated and affect the query and thus the resulting values for measures.

For example, you have a list of members in which the aggregate sums to 100. Over time, more members meet the set filter criteria, which increases the aggregate sum to 200.

Column Filters

Following are the ways to create filters −

Create a Named Column Filter

Go to Oracle Business Intelligence homepage → New menu → Select filter. The Select Subject Area dialog is displayed.

From the Select Subject Area dialog, choose the subject area for which you want to create a filter. The “Filter editor” is displayed from the “Subject Areas pane”. Double-click the column for which you want to create the filter. New Filter dialog is displayed.

Create an Inline Filter

Either create an analysis or access an existing analysis for which you want to create a filter.

Click the Criteria tab → Locate the “Filters pane” → Click create a filter for the current subject area button. The analysis selected columns are displayed in the cascading menu.

Select a column name from the menu or select the More Columns option to access the “Select Column dialog” from which you can select any column from the subject area.

Once you select a column, the “New Filter dialog” is displayed.

OBIEE – Views

Oracle BI Enterprise Edition enables you to look at results of analyses in a meaningful way using its presentation capabilities. Different types of views can be added, such as graphs and pivot tables that allow drilling down to more detailed information and many more options like using filters, etc.

The results of the analysis is displayed using a table/Pivot table view and depends on the type of columns that the analysis contains −

Table view is used if the analysis contains only attribute columns/only measure columns or a combination of both.
Pivot table is the default view if the analysis contains at least one hierarchical column.
A title view displays the name of the saved analysis.
You can edit or delete an existing view, add another view to an analysis and can also combine views.

Types of Views

There are different types of views available −

Sr.No	Views & Description
1	Title Title view displays a title, a subtitle, a logo, a link to a custom online help page and timestamps to the results.
2	Table Table view is used to display results in a visual representation of data organized by rows and columns. It provides a summary view of data and enables users to see different views of data by dragging and dropping rows and columns.
3	Pivot Table It displays results in a pivot table, which provides a summary view of data in cross-tab format and enables users to see different views of data by dragging and dropping rows and columns. Pivot tables and standard tables are similar in structure but Pivot table can contain column groups and can also display multiple levels of both row and column headings. Pivot table cell contains a unique value. Pivot table is more efficient than a row-based table. It is best suited for displaying a large quantity of data, for browsing data hierarchically, and for trend analysis.
4	Performance Tile Performance tiles are used to display a single aggregate measure value in a manner that is visually simple but provides a summary metrics to the user that will likely be presented in more detail within a dashboard view. Performance tiles are used to focus the user’s attention on simple, need-to-know facts directly and prominently on the tile. Communicate status through simple formatting by using color, labels, and limited styles, or through conditional formatting of the background color or measure value to make the tile visually prominent. For example, if revenue is not tracking to target, the revenue value may appear in red. Respond to prompts, filters, and user roles and permissions by making them relevant to the user and their context. Support a single, aggregate or calculated value.
5	Treemap Tree map are used to display a space-constrained, 2-d visualization for hierarchical structures with multiple levels. Treemaps are limited by a predefined area and display two levels of data. Contain rectangular tiles. The size of the tile is based on a measure, and the color of the tile is based on a second measure. Treemap are similar to a scatter plot graphs in that the map area is constrained, and the graph allows you to visualize large quantities of data and quickly identify trends and anomalies within that data.
6	Trellis Trellis displays multi-dimensional data shown as a set of cells in a grid form and where each cell represents a subset of data using a particular graph type. The trellis view has two subtypes − Simple Trellis and Advanced Trellis. Simple trellis views are ideal for displaying multiple graphs that enable comparison of like to like. Advanced trellis views are ideal for displaying spark graphs that show a trend. A simple trellis displays a single inner graph type, Example − a grid of multiple Bar graphs. An advanced trellis displays a different inner graph type for each measure. Example: A mixture of Spark Line graphs and Spark Bar graphs, alongside numbers.
7	Graph Graph displays numeric information visually which makes it easier to understand large quantities of data. Graphs often reveal patterns and trends that text-based displays cannot. A graph is displayed on a background, called the graph canvas.
8	Gauge Gauge are used to show a single data value. Cos of its compact size, a gauge is often more effective than a graph for displaying a single data value Gauges identify problems in data. A gauge usually plots one data point with an indication of whether that point falls in an acceptable or unacceptable range. Thus, gauges are useful for showing performance against goals. A gauge or gauge set is displayed on a background, called the gauge canvas.
9	Funnel Funnel displays results in 3D graph that represents target and actual values using volume, level, and color. Funnel graphs are used to graphically represent data that changes over different periods or stages. Example: Funnel graphs are often used to represent the volume of sales over a quarter. Funnel graphs are well suited for showing actual compared to targets for data where the target is known to decrease (or increase) significantly per stage, such as a sales pipeline.
10	Map view Map view is used to display results overlain on a map. Depending on the data, the results can be overlain on top of a map as formats such as images, color fill areas, bar and pie graphs, and variably sized markers.
11	Filters Filter are used to displays the filters in effect for an analysis. Filters allows you to add condition to an analysis to obtain results that answer a particular question. Filters are applied before the query is aggregated.
12	Selection Steps Selection steps are used to displays the selection steps in effect for an analysis. Selection steps, like filters, allow you to obtain results that answer particular questions. Selection steps are applied after the query is aggregated.
13	Column Selector Column selector is a set of drop-down lists that contain pre-selected columns. Users can dynamically select columns and change the data that is displayed in the views of the analysis.
14	View Selector A view selector is a drop-down list from which users can select a specific view of the results from among the saved views.
15	Legend It enables you to document the meaning of special formatting used in results-meaning of custom colors applied to gauges.
16	Narrative It displays the results as one or more paragraphs of text.
17	Ticker It displays the results as a ticker or marquee, similar in style to the stock tickers that run across many financial and news sites on the Internet. You can also control what information is presented and how it scrolls across the page.
18	Static Text You can use HTML to add banners, tickers, ActiveX objects, Java applets, links, instructions, descriptions, graphics, etc. in the results.
19	Logical SQL It displays the SQL statement that is generated for an analysis. This view is useful for trainers and administrators, and is usually not included in results for typical users. You cannot modify this view, except to format its container or to delete it.
20	Create Segment It is used to display a Create Segment link in the results.
21	Create Target List It is used to display a create target list link in the results. Users can click this link to create a target list, based on the results data, in their Oracle’s Siebel operational application. This view is for users of Oracle’s Siebel Life Sciences operational application integrated with Oracle’s Siebel Life Sciences Analytics applications.

All view types except logical SQL view can be edited. Each view has its own editor in which you can perform edit task.

Each view editor contains a unique functionality for that view type but might also contain functionality that is the same across view types.

Edit a View

Open the analysis that contains the view to edit. Click the “Analysis editor: Results tab.”

Click the Edit View button for the view. View editors is displayed. Now, using the editor for the view, make the required edits. Click done and then save the view.

Delete a View

You can delete a view from −

A compound layout − If you remove a view from a compound layout, it is only removed from the compound layout and not from the analysis.
An analysis − If you remove a view from an analysis, it removes the view from the analysis and also from any compound layout to which it had been added.

Remove a View

If you want to remove a view from −

A compound layout − In the view in the Compound Layout → click the Remove View from Compound Layout button.
An analysis − In the Views pane → select the view and then click the Remove View from Analysis toolbar button.

So, this brings us to the end of blog. This Tecklearn ‘Views and Filters in OBIEE’ blog helps you with commonly asked questions if you are looking out for a job in Oracle BI. If you wish to learn OBIEE and build a career in Business Intelligence domain, then check out our interactive, Oracle Business Intelligence Enterprise Edition (OBIEE) Training, that comes with 24*7 support to guide you throughout your learning period. Please find the link for course details:https://www.tecklearn.com/course/oracle-business-intelligence-enterprise-edition-training-and-certification/

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About the Course

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What you will Learn in this Course?

Data Modelling and Data Warehousing Concepts

Introduction to Oracle Business Intelligence Enterprise Edition (OBIEE)
Data models
Data warehousing
Data modelling implications and the impact of Data modelling on business intelligence

Business Intelligence Concepts

Overview of Business Intelligence
Description of BI Stack: BI technology, BI Server and BI Scheduler
Need for reporting in business
Difference between OLTP and OLAP
Multidimensional and relational analytical processing

OBIEE Installation

OBIEE Installation (12c)
Oracle Business Intelligence Suite
Architecture of OBIEE
Key features and components

Online Analytical Processing (OLAP)

Concept of Online Analytical Processing
Significance of OLAP in business intelligence life cycle
Star Schema and Designing with Star Schema
Enterprise information model
Snow flake and constellation

Oracle BI Repository

What is Oracle Business Intelligence Repository?
Directory structure installation, services,
Analytics and interactive reporting,
Dashboard creation and multiple report creation

Business Intelligence Repository Business Model

How to build a Business Model and Mapping Layer in BI Repository
Data format, Conditional format, Removing filters,
Report Saving
Creation of new folder
Working with the Enterprise Manager
Testing and validation of the Repository
Understanding the process of Cache disabling
Dashboard prompt and filtering

Dashboard Creation

Creation and Setup of OBIEE Dashboard
Basics of OBIEEE dashboard
Deploying Dashboard Builder for building Dashboards
Edit, Share and Save options in Dashboard analysis
Process of Cache creation and clearing
ODBC functions
Logical Table Source, Summary and Detail Report

OBIEE Repository

OBIEE Repository
Creation of Test Report and adding calculations
Deployment of OBIEE analysis
Repository variables, session and presentation variables

OBIEE Security & Management

Securing the Oracle Business Intelligence Suite with Enterprise Manager
Creation of alerts and notifications
Administration, Maintenance and Grouping
Types of security in OBIEE
Task and folder level security

Differences between OBIEE 11g and 12c

Hands on Variables

New Features of OBIEE 12c

Repository Development
Catalog Development
Deployment-Online
RPD Deployment

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