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• Index
• Appendix A. Bibliography
• Summary
• Further learning
• Model evaluation
• Using Rattle to forecast the demand

• Index 更新時間：2021-07-02 20:12:29
• Appendix A. Bibliography
• Summary
• Further learning
• Model evaluation
• Using Rattle to forecast the demand
• Creating a Qlik Sense App to control the activity
• Exploring the data with Qlik Sense
• Understanding the bike rental problem
• Chapter 9. Developing a Complete Application
• Summary
• Further learning
• Data storytelling with Qlik Sense
• Data analysis data applications and dashboards
• Data visualization in Qlik Sense
• Chapter 8. Visualizations Data Applications Dashboards and Data Storytelling
• Summary
• Further learning
• Measuring the performance of classifiers
• Regression performance
• Cross-validation
• Chapter 7. Model Evaluation
• Summary
• Further learning
• Other models
• Ensemble classifiers
• Using a Decision Tree to classify credit risks
• Underfitting and overfitting
• Entropy and information gain
• Decision Tree Learning
• Partitioning datasets and model optimization
• Chapter 6. Decision Trees and Other Supervised Learning Methods
• Summary
• Further learning
• Machine learning – unsupervised and supervised learning
• Chapter 5. Clustering and Other Unsupervised Learning Methods
• Summary
• Further learning
• Analyzing your data
• Creating charts
• Associative logic
• Creating a simple data app
• Loading data and creating a data model
• Customer segmentation and customer buying behavior
• Chapter 4. Creating Your First Qlik Sense Application
• Summary
• Further learning
• Correlations among input variables
• Visualizing distributions
• Text summaries
• Chapter 3. Exploring and Understanding Your Data
• Summary
• Further learning
• Exporting data
• Cleaning up
• Transforming data
• Loading data
• Datasets observations and variables
• Chapter 2. Preparing Your Data
• Summary
• Further learning
• Exploring Qlik Sense Desktop
• Installing Qlik Sense Desktop
• Downloading and installing Rattle
• Installing the environment
• Introducing R Rattle and Qlik Sense Desktop
• Purpose of the book
• Analytics predictive analytics and data visualization
• Chapter 1. Getting Ready with Predictive Analytics
• Part 3. Module 3
• Keyboard shortcuts in Qlik Sense Desktop
• Appendix A. Appendix
• Conclusion
• Using smart data load profiling
• Using Smart Search
• Creating dynamic charts in Qlik Sense
• Using the Qlik DataMarket
• Embedding Qlik Sense application on a website using a single configurator
• Using Qlik Dev Hub to generate mashups
• Using Extension editor in Qlik Dev Hub
• Using the Qlik Dev Hub in Qlik Sense 2.1.1
• Exporting stories to MS PowerPoint
• Defining variables in Qlik Sense
• Using the visual exploration capability in Qlik Sense 2.1.1
• Introduction
• Chapter 8. What's New in Version 2.1.1?
• Using data with extensions
• Creating custom components within Qlik Sense visualizations
• Defining a Properties panel in Qlik Sense visualizations
• Creating an HTML visualization extension for Qlik Sense
• Introduction
• Chapter 7. Extensions in Qlik Sense
• Using the element functions P() and E() in Set Analysis
• Capturing a list of field values using a concat() function in Set Analysis
• Using search strings inside a set modifier
• Creating a multi-measure expression in Set Analysis
• Using embedded functions in Set Analysis
• Using comparison sets in Set Analysis
• Point in time using Set Analysis
• Using the = sign with variables in Set Analysis
• Using flags in Set Analysis
• Cracking the syntax for Set Analysis
• Introduction
• Chapter 6. Set Analysis
• Using the Peek() function to create a Trial Balance sheet
• Using the Peek() function to create a currency Exchange Rate Calendar
• Using the For Each loop to extract files from a folder
• Setting up a moving annual total figure
• Using the Declare and Derive functions to generate Calendar fields
• Using the FirstSortedValue() function to identify the median in a quartile range
• Using the Fractile() function to generate quartiles
• Using the Rangesum() function to plot cumulative figures in trendline charts
• Using the Minstring() function to calculate the age of the oldest case in a queue
• Using the Concat() function to display a string of field values as a dimension
• Using the NetworkDays() function to calculate the working days in a calendar month
• Using the Previous() function to identify the latest record for a dimensional value
• Using an extended interval match to handle Slowly Changing Dimensions
• Introduction
• Chapter 5. Useful Functions
• Navigating many data points in a scatter chart
• Adding thumbnails – a clear environment
• Applying limitations to charts
• Creating text and images
• Adding Reference Lines to trendline charts
• Creating dimensionless bar charts in Qlik Sense
• Creating Tree Maps
• Effectively using the KPI object in Qlik Sense
• Reference lines in Sales versus Target gauge chart
• Creating geo maps in Qlik Sense
• Publishing a Qlik Sense application to Qlik Sense cloud
• Creating private approved and community sheets
• Publishing a Qlik Sense application created in Qlik Sense desktop
• Introduction
• Chapter 4. Managing Apps and User Interface
• Using the Concat function to store multiple field values in a single cell
• Using a For Each loop to load data from multiple files
• Optimizing the reload time of the application
• Optimizing the UI calculation speed
• How to use sub routines in Qlik Sense
• Packaging the code in script files
• Efficiently debugging the script
• Structuring the script
• Introduction
• Chapter 3. Scripting
• Structuring visualizations
• Distribution
• Comparison
• Relationships
• Composition
• Using the ColorMix1 function
• Associating persistent colors to field values
• Highlighting the performance measure in a bar chart
• Adding embedded sheets to the story
• Creating and adding content to a story
• Creating Snapshots
• Introduction
• Chapter 2. Visualizations
• Using a Master Library in the Edit mode
• Creating a Master Library from the Data model viewer
• Previewing data in the Data model viewer
• Invoking help while in the data load editor or the expression editor
• Extracting data from custom databases
• Activating the Legacy Mode in Qlik Sense desktop
• Extracting data from Web Files
• Extracting data from databases and data files
• Introduction
• Chapter 1. Getting Started with the Data
• Part 2. Module 2
• Summary
• How the application was developed
• Application features
• Problem analysis
• Chapter 13. Demographic Data Discovery
• Summary
• Developing the application
• Application features
• The business problem
• Chapter 12. Travel Expense Discovery
• Summary
• How the application was developed
• Application features
• The business problem
• Chapter 11. Human Resource Discovery
• Summary
• Application features
• The business problem
• Chapter 10. Sales Discovery
• Summary
• Security
• Management and monitoring
• Deployment and licensing
• The Qlik Sense architecture
• Chapter 9. Administering Qlik Sense
• Summary
• Developer community – Qlik Branch
• Qlik Dev Hub
• Chapter 8. Extending the Qlik Analytic Platform
• Summary
• Adding the QlikMarket data
• Using the Qlik DataMarket content
• Using Qlik Sense apps in the cloud
• Why use the cloud?
• Chapter 7. Qlik Sense Apps in the Cloud
• Summary
• The data model viewer
• Structuring your data
• The Qlik Sense data model
• The QIX engine
• Chapter 6. Building Qlik Sense Data Models
• Summary
• Publishing your apps
• Migrating applications from QlikView to Qlik Sense
• Best practices in data visualization
• The application library
• The analysis interface—sheets and visualizations
• Loading your data
• Getting started with the app creation
• Preparations and requirements
• Chapter 5. Authoring Engaging Applications
• Summary
• Creating and sharing stories
• Realities of the data discovery contributor
• Chapter 4. Contributing to Data Discovery
• Summary
• Data discovery consumption requirements
• Chapter 3. Empowering Next Generation Data Discovery Consumers
• Summary
• Overview of an application's life cycle
• Chapter 2. Overview of a Qlik Sense Application's Life Cycle
• Summary
• Data discovery—the evolution of BI
• The Qlik way
• What is data discovery?
• Qlik Sense and the QlikView.Next project
• Continuing disruption
• Chapter 1. Qlik Sense and Data Discovery
• Part 1. Module 1
• Preface
• Credits
• 版權信息
• 封面

• 封面
• 版權信息
• Credits
• Preface
• Part 1. Module 1
• Chapter 1. Qlik Sense and Data Discovery
• Continuing disruption
• Qlik Sense and the QlikView.Next project
• What is data discovery?
• The Qlik way
• Data discovery—the evolution of BI
• Summary
• Chapter 2. Overview of a Qlik Sense Application's Life Cycle
• Overview of an application's life cycle
• Summary
• Chapter 3. Empowering Next Generation Data Discovery Consumers
• Data discovery consumption requirements
• Summary
• Chapter 4. Contributing to Data Discovery
• Realities of the data discovery contributor
• Creating and sharing stories
• Summary
• Chapter 5. Authoring Engaging Applications
• Preparations and requirements
• Getting started with the app creation
• Loading your data
• The analysis interface—sheets and visualizations
• The application library
• Best practices in data visualization
• Migrating applications from QlikView to Qlik Sense
• Publishing your apps
• Summary
• Chapter 6. Building Qlik Sense Data Models
• The QIX engine
• The Qlik Sense data model
• Structuring your data
• The data model viewer
• Summary
• Chapter 7. Qlik Sense Apps in the Cloud
• Why use the cloud?
• Using Qlik Sense apps in the cloud
• Using the Qlik DataMarket content
• Adding the QlikMarket data
• Summary
• Chapter 8. Extending the Qlik Analytic Platform
• Qlik Dev Hub
• Developer community – Qlik Branch
• Summary
• Chapter 9. Administering Qlik Sense
• The Qlik Sense architecture
• Deployment and licensing
• Management and monitoring
• Security
• Summary
• Chapter 10. Sales Discovery
• The business problem
• Application features
• Summary
• Chapter 11. Human Resource Discovery
• The business problem
• Application features
• How the application was developed
• Summary
• Chapter 12. Travel Expense Discovery
• The business problem
• Application features
• Developing the application
• Summary
• Chapter 13. Demographic Data Discovery
• Problem analysis
• Application features
• How the application was developed
• Summary
• Part 2. Module 2
• Chapter 1. Getting Started with the Data
• Introduction
• Extracting data from databases and data files
• Extracting data from Web Files
• Activating the Legacy Mode in Qlik Sense desktop
• Extracting data from custom databases
• Invoking help while in the data load editor or the expression editor
• Previewing data in the Data model viewer
• Creating a Master Library from the Data model viewer
• Using a Master Library in the Edit mode
• Chapter 2. Visualizations
• Introduction
• Creating Snapshots
• Creating and adding content to a story
• Adding embedded sheets to the story
• Highlighting the performance measure in a bar chart
• Associating persistent colors to field values
• Using the ColorMix1 function
• Composition
• Relationships
• Comparison
• Distribution
• Structuring visualizations
• Chapter 3. Scripting
• Introduction
• Structuring the script
• Efficiently debugging the script
• Packaging the code in script files
• How to use sub routines in Qlik Sense
• Optimizing the UI calculation speed
• Optimizing the reload time of the application
• Using a For Each loop to load data from multiple files
• Using the Concat function to store multiple field values in a single cell
• Chapter 4. Managing Apps and User Interface
• Introduction
• Publishing a Qlik Sense application created in Qlik Sense desktop
• Creating private approved and community sheets
• Publishing a Qlik Sense application to Qlik Sense cloud
• Creating geo maps in Qlik Sense
• Reference lines in Sales versus Target gauge chart
• Effectively using the KPI object in Qlik Sense
• Creating Tree Maps
• Creating dimensionless bar charts in Qlik Sense
• Adding Reference Lines to trendline charts
• Creating text and images
• Applying limitations to charts
• Adding thumbnails – a clear environment
• Navigating many data points in a scatter chart
• Chapter 5. Useful Functions
• Introduction
• Using an extended interval match to handle Slowly Changing Dimensions
• Using the Previous() function to identify the latest record for a dimensional value
• Using the NetworkDays() function to calculate the working days in a calendar month
• Using the Concat() function to display a string of field values as a dimension
• Using the Minstring() function to calculate the age of the oldest case in a queue
• Using the Rangesum() function to plot cumulative figures in trendline charts
• Using the Fractile() function to generate quartiles
• Using the FirstSortedValue() function to identify the median in a quartile range
• Using the Declare and Derive functions to generate Calendar fields
• Setting up a moving annual total figure
• Using the For Each loop to extract files from a folder
• Using the Peek() function to create a currency Exchange Rate Calendar
• Using the Peek() function to create a Trial Balance sheet
• Chapter 6. Set Analysis
• Introduction
• Cracking the syntax for Set Analysis
• Using flags in Set Analysis
• Using the = sign with variables in Set Analysis
• Point in time using Set Analysis
• Using comparison sets in Set Analysis
• Using embedded functions in Set Analysis
• Creating a multi-measure expression in Set Analysis
• Using search strings inside a set modifier
• Capturing a list of field values using a concat() function in Set Analysis
• Using the element functions P() and E() in Set Analysis
• Chapter 7. Extensions in Qlik Sense
• Introduction
• Creating an HTML visualization extension for Qlik Sense
• Defining a Properties panel in Qlik Sense visualizations
• Creating custom components within Qlik Sense visualizations
• Using data with extensions
• Chapter 8. What's New in Version 2.1.1?
• Introduction
• Using the visual exploration capability in Qlik Sense 2.1.1
• Defining variables in Qlik Sense
• Exporting stories to MS PowerPoint
• Using the Qlik Dev Hub in Qlik Sense 2.1.1
• Using Extension editor in Qlik Dev Hub
• Using Qlik Dev Hub to generate mashups
• Embedding Qlik Sense application on a website using a single configurator
• Using the Qlik DataMarket
• Creating dynamic charts in Qlik Sense
• Using Smart Search
• Using smart data load profiling
• Conclusion
• Appendix A. Appendix
• Keyboard shortcuts in Qlik Sense Desktop
• Part 3. Module 3
• Chapter 1. Getting Ready with Predictive Analytics
• Analytics predictive analytics and data visualization
• Purpose of the book
• Introducing R Rattle and Qlik Sense Desktop
• Installing the environment
• Downloading and installing Rattle
• Installing Qlik Sense Desktop
• Exploring Qlik Sense Desktop
• Further learning
• Summary
• Chapter 2. Preparing Your Data
• Datasets observations and variables
• Loading data
• Transforming data
• Cleaning up
• Exporting data
• Further learning
• Summary
• Chapter 3. Exploring and Understanding Your Data
• Text summaries
• Visualizing distributions
• Correlations among input variables
• Further learning
• Summary
• Chapter 4. Creating Your First Qlik Sense Application
• Customer segmentation and customer buying behavior
• Loading data and creating a data model
• Creating a simple data app
• Associative logic
• Creating charts
• Analyzing your data
• Further learning
• Summary
• Chapter 5. Clustering and Other Unsupervised Learning Methods
• Machine learning – unsupervised and supervised learning
• Further learning
• Summary
• Chapter 6. Decision Trees and Other Supervised Learning Methods
• Partitioning datasets and model optimization
• Decision Tree Learning
• Entropy and information gain
• Underfitting and overfitting
• Using a Decision Tree to classify credit risks
• Ensemble classifiers
• Other models
• Further learning
• Summary
• Chapter 7. Model Evaluation
• Cross-validation
• Regression performance
• Measuring the performance of classifiers
• Further learning
• Summary
• Chapter 8. Visualizations Data Applications Dashboards and Data Storytelling
• Data visualization in Qlik Sense
• Data analysis data applications and dashboards
• Data storytelling with Qlik Sense
• Further learning
• Summary
• Chapter 9. Developing a Complete Application
• Understanding the bike rental problem
• Exploring the data with Qlik Sense
• Creating a Qlik Sense App to control the activity
• Using Rattle to forecast the demand
• Model evaluation
• Further learning
• Summary
• Appendix A. Bibliography
• Index 更新時間：2021-07-02 20:12:29