Table of Contents
- Title and Copyright Information
- Preface
- 1 Get Started with Oracle Analytics Desktop
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2
Connect to Data Sources
- About Data Sources
- Manage Connections to Data Sources
- Create a connection for an Oracle Database
- Connect to Oracle Applications
- Create a Connection to Oracle Essbase
- Connect to Dropbox
- Connect to Google Drive or Google Analytics
- Create JDBC Connections
- Create Generic ODBC Connections
- Connect to Oracle Autonomous Data Warehouse
- Connect to Oracle Autonomous Transaction Processing
- Connect to Oracle Talent Acquisition Cloud
- Connect to Snowflake Data Warehouse
- Connecting to NetSuite
- 3 Add Data Sets
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4
Prepare Your Data Set for Analysis
- Typical Workflow to Prepare Your Data Set for Analysis
- About Data Preparation
- Data Profiles and Semantic Recommendations
- Accept Enrichment Recommendations
- Transform Data Using Column Menu Options
- Convert Text Columns to Date or Time Columns
- Adjust the Display Format of Date or Time Columns
- General Custom Format Strings
- Create a Bin Column When You Prepare Data
- Edit the Column Properties
- Edit the Data Preparation Script
- Add Columns in Data Preparation
- Transform Data Using Replace
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5
Manage Data and Data Sets
- Typical Workflow to Manage Added Data
- Manage Data Sets
- Types of Data You Can Refresh
- Refresh Data in a Data Set
- Update Details of Data that You Added
- Delete Data Sets
- Rename a Data Set
- Duplicate Data Sets
- Blend Data that You Added
- About Mismatched Values in Blended Data
- Change Data Blending in a Project
- View and Edit Object Properties
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6
Visualize and Analyze Data
- Typical Workflow to Visualize Data
- Create a Project and Add Data Sets
- Build a Visualization by Adding Data from Data Panel
- Use Advanced Analytics Functions
- Use Spark Charts to Examine Trends
- Create Calculated Data Elements in a Data Set
- Sort Data in Visualizations
- Undo and Redo Edits
- Refresh Data in a Project
- Pause Data Queries in a Project
- Adjust the Visualize Canvas Layout and Properties
- Copy and Paste a Visualization or Canvas
- Change Visualization Types
- Adjust Visualization Properties
- Apply Color to Visualizations
- Format Numeric Values of Columns
- Set Currency Symbols for Visualizations
- Format Numeric Values of Visualizations
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Apply Map Backgrounds and Map Layers to Enhance Visualizations
- About Map Backgrounds
- Enhance Visualizations with Map Backgrounds
- Use Different Map Backgrounds in a Project
- Interpret Data Values with Color and Size in Map Visualizations
- Add Custom Map Layers
- Update Custom Map Layers
- Apply Multiple Data Layers to a Single Map Visualization
- Use an Image as a Map Background and Draw Map Layer Shapes on the Image
- Assign a Map Layer to a Data Column
- Auto Focus on Data for a Map Visualization
- Review Location Matches for a Map Visualization
- Create Heatmap Layers on a Map Visualization
- Create Cluster Layers on a Map Visualization
- Represent Point Data With Custom Icons on a Map
- Select Points or Area on a Map
- Represent Line Data Using Size and Color on a Map
- Make Map Layers and Backgrounds Available to Users
- Use a Map Background as the Default
- Add Map Backgrounds
- Sort and Select Data in Visualization Canvases
- Replace a Data Set in a Project
- Remove a Data Set from a Project
- Analyze Data with Explain
- About Warnings for Data Issues in Visualizations
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7
Create and Apply Filters
- Typical Workflow to Create and Apply Filters
- About Filters and Filter Types
- How Data Sets Interact with Filters
- How the Number of Data Sets Affects Filters
- Synchronize Visualizations in a Project
- About Automatically Applied Filters
- Create Filters on a Project
- Create Filters on a Visualization
- Change the Scope of Filters Between the Main Filter Bar and Visualizations
- Use a Visualization as a Filter
- Move Filter Panels
- Apply Range Filters
- Apply Top Bottom N Filters
- Apply List Filters
- Apply Date Range Filters
- Apply Relative Time Filters
- Build Expression Filters
- Add an On-Canvas Filter
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8
Use Other Functions to Visualize Data
- Typical Workflow to Prepare, Connect, and Search Artifacts
- Build Stories
- Add Notes
- Identify Content with Thumbnails
- Manage Custom Plug-ins
- Compose Expressions
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Use Data Actions to Connect to
Canvases, External URLs, and Use in Publisher Reports
- Create Data Actions to Connect Visualization Canvases
- Create Data Actions to Connect to External URLs from Visualization Canvases
- Create Data Actions to Connect to REST APIs from Visualization Canvases
- Use Data Actions to Connect to Oracle Business Intelligence Publisher Reports
- Invoke Data Actions from Visualization Canvases
- Visualize Data from the Home Page
- Find Data, Projects, and Visualizations
- Save Your Changes Automatically
- Sort the Items in a Page
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9
Create Custom Data Action
Plug-ins
- About Data Action Plug-ins and the Data Actions Framework
- Choose the Best Data Action Class to Extend
- Generate Data Action Plug-ins from a Template
- Generated Folders and Files
- Extend a Data Action Base Class
- Choose Which Data Action Inherited Methods to Override
- Test, Package, and Install Your Data Action
- Use an Upgrade Handler for Knockout Model Changes
- Upgrade Data Action Plug-ins
- Data Action Plug-in File Reference
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10
Use Oracle Analytics Predictive Models and Oracle Machine Learning Models
- Create and Use Oracle Analytics Predictive Models
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Register and Use Oracle Machine Learning Models
- How Can I Use Oracle Machine Learning Models in Oracle Analytics?
- Typical Workflow to Register and Use Oracle Machine Learning Models
- Register Oracle Machine Learning Models in Oracle Analytics
- Inspect Registered Oracle Machine Learning Models
- Visualize a Registered Oracle Machine Learning Model's View
- Apply a Predictive or Registered Oracle Machine Learning Model to a Data Set
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11
Curate Your Data Using Data
Flows
- Typical Workflow to Curate Data with Data Flows
- About Data Flows
- Create a Data Flow
- Run a Data Flow
- Run a Saved Data Flow
- Reuse a Data Flow
- Apply Incremental Processing to a Data Flow
- Modify Parameter Prompts When You Run a Data Flow
- Customize the Names and Descriptions of Data Flow Steps
- Create a Sequence of Data Flows
- Manage Your Data Flows
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Using Steps
- Add Columns in a Data Flow
- Add Data in a Data Flow
- Add Aggregates to a Data Flow
- Create a Bin Column in a Data Flow
- Create Multiple Pipelines in a Data Flow Using a Branch
- Create and Customize an Essbase Cube in a Data Flow
- Add Cumulative Values to a Data Flow
- Add Database Analytics to a Data Flow
- Filter Your Data in a Data Flow
- Create a Group in a Data Flow
- Add a Join in a Data Flow
- Merge Columns in a Data Flow
- Rename Columns in a Data Flow
- Save Output Data from a Data Flow
- Save Model
- Select Columns to Include in a Data Flow
- Add a Sentiment Analysis to a Data Flow
- Split Columns in a Data Flow
- Add a Time Series Forecast to a Data Flow
- Train a Binary Classifier Model in a Data Flow
- Train a Clustering Model in a Data Flow
- Train a Multi-Classifier Model in a Data Flow
- Train a Numeric Prediction Model in a Data Flow
- Transform Data in a Data Flow
- Merge Rows in a Data Flow
- 12 Import and Share
- A Frequently Asked Questions
- B Troubleshoot Visualization Issues
- C Accessibility Features and Tips
- D Data Sources and Data Types Reference
- E Data Preparation Reference
- F Expression Editor Reference
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G
Oracle Analytics Desktop SDK Reference
- Oracle Analytics Desktop SDK
- Create the Visualization Plug-in Development Environment
- Create a Skeleton Visualization Plug-in
- Create a Skeleton Skin or Unclassified Plug-in
- Develop a Visualization Plug-in
- Run in SDK Mode and Test the Plug-in
- Validate the Visualization Plug-in
- Build, Package, and Deploy the Visualization Plug-in
- Delete Plug-ins from the Development Environment