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Hands-On Business Intelligence with Qlik Sense
QlikSenseallowsyoutoexploresimple-to-complexdatatorevealhiddeninsightsanddatarelationshipstomakebusiness-drivendecisions.Hands-OnBusinessIntelligencewithQlikSensebeginsbyhelpingyougettogripswithunderlyingQlikconceptsandgivesyouanoverviewofallQlikSense’sfeatures.Youwilllearnadvancedmodelingtechniquesandlearnhowtoanalyzethedataloadedusingavarietyofvisualizationobjects.You’llalsobetrainedonhowtoshareappsthroughQlikSenseEnterpriseandQlikSenseCloudandhowtoperformaggregationwithAGGR.Asyouprogressthroughthechapters,you’llexplorethestoriesfeaturetocreatedata-drivenpresentationsandupdateanexistingstory.ThisbookwillguideyouthroughtheGeoAnalyticsfeaturewiththegeo-mappingobjectandGeoAnalyticsconnector.Furthermore,you’lllearnabouttheself-serviceanalyticsfeaturesandperformdataforecastingusingadvancedanalytics.Lastly,you’lldeployQlikSenseappsformobileandtablet.Bytheendofthisbook,youwillbewell-equippedtorunsuccessfulbusinessintelligenceapplicationsusingQlikSense'sfunctionality,datamodelingtechniques,andvisualizationbestpractices.
最新章節
- Leave a review - let other readers know what you think
- Other Books You May Enjoy
- Summary
- Preparing the Sales Analysis app for offline usage
- Choosing the right client
- The Quick view sheet
品牌：中圖公司
上架時間：2021-07-02 12:25:44
出版社：Packt Publishing
本書數字版權由中圖公司提供，并由其授權上海閱文信息技術有限公司制作發行
- Leave a review - let other readers know what you think 更新時間：2021-07-02 13:06:12
- Other Books You May Enjoy
- Summary
- Preparing the Sales Analysis app for offline usage
- Choosing the right client
- The Quick view sheet
- Reviewing the responsive design of the Sales Analysis application
- Responsive object design
- Responsive layouts
- Setting up the Sales Analysis app for mobile usage
- Technical requirements
- Deploying Qlik Sense Apps for Mobile/Tablets
- Further reading
- Questions
- Summary
- Using the Python SSE in your apps
- Qlik Sense Enterprise
- Qlik Sense Desktop
- Configuring Qlik Sense
- Using a Python extension
- Installing TensorFlow
- Updating Python pip
- Installing Python
- Preparing your Python environment
- Using the R extension in a Qlik Sense application
- Starting all services
- Qlik Sense Enterprise
- Qlik Sense Desktop
- Configuring Qlik Sense
- Installing the SSE plugin
- Installing more packages
- Installing Rserve()
- Installing R
- Preparing your R environment
- SSE functions
- How SSE works
- Qlik approach to data science platforms
- Qlik Sense Engine and Server Side Extensions
- Technical requirements
- Data Forecasting Using Advanced Analytics
- Further reading
- Summary
- Publishing changes to a published application
- Sharing the app with users
- Editing the application with multiple users
- Managing members
- Co-creating applications in Qlik Sense Cloud Business
- Approving sheets to add them to a baseline
- Sharing insights with community sheets
- Creating a new sheet in a published app
- Publishing an application
- Creating self-service analytics
- Technical requirements
- Working with Self-Service Analytics
- Further reading
- Summary
- Info Bubble
- Label
- Adding more information to the map
- Heatmap layer
- Area layer
- Adding layers
- Adding the base map
- Loading geographical data
- Creating a map
- Concepts of GeoAnalytics
- Technical requirements
- Creating a Native Map Using GeoAnalytics
- Further reading
- Summary
- Testing our on-demand application
- Integrating the summarized and detailed applications
- Creating a dynamic SQL
- Adding restrictions
- Recovering a long list of selected (or possible) values
- Binding expressions in on-demand template apps
- Building the detailed application
- Adding a script to retrieve data
- Creating a connection
- Building a summarized application
- Configuring Qlik Sense for ODAG applications
- Setting up a Google BigQuery account
- How Qlik Sense handles large volumes of data
- Technical requirements
- Engaging On-Demand App Generation
- Section 4: Additional Features
- Further reading
- Summary
- Sharing stories
- Editing your story
- Creating stories
- Planning and organizing your presentation
- Creating snapshots
- An overview of stories
- Creating Data Stories
- Further reading
- Summary
- Selecting a specific country for comparison
- Leveraging Set Analysis for in-calculation selection
- Calculating the top sales product over each category
- Using AGGR for advanced aggregation
- Calculating sales variance year over year
- Using some useful inter-record functions
- Calculating the relative share over a dimension
- Calculating the relative share over the total
- Using TOTAL for aggregation scope
- Condition to filter data on a measure
- Condition to show a different calculation
- Condition to show a text message
- Creating calculations with conditions
- Technical requirements
- Interacting with Advanced Expressions
- Summary
- Adding a default filter pane
- Creating a new sheet
- Creating a reporting sheet
- Creating a scatter plot
- Creating a line chart by OrderMonthYear and Category
- Creating a bar chart with a drill-down dimension
- Adding KPI visualizations
- Adding a filter pane
- Creating a new sheet for product analysis
- Creating a product analysis sheet
- Creating a table chart with customer information
- Creating a combo chart for Pareto (80/20) analysis
- Adding KPI visualizations
- Adding a filter pane with main dimensions
- Creating a new sheet for customer analysis
- Creating a customer analysis sheet
- Creating the analysis sheets
- Creating a filter pane with Order Year and Order Month fields
- Creating the geographical map of sales by country
- Creating a bar chart with Sales $ by Top 10 Customers
- Creating a pie chart with Sales $ by Categories
- Creating KPI visualizations
- Creating a new sheet for the dashboard
- Creating the dashboard
- Creating the dashboard sheet
- Technical requirements
- Creating a Sales Analysis App Using Qlik Sense
- Further reading
- Questions
- Summary
- Calculation expressions
- Creating master visualizations
- Creating master measures
- Creating master dimensions
- Creating Master items
- Creating visualizations manually
- Creating visualizations using chart suggestions
- Generating visualizations using Insights Advisor for selected fields
- Generating visualizations using Insights Advisor
- Getting started
- Creating visualization objects
- Understanding the DAR methodology
- Toolbars
- Application overview
- Technical requirements
- Working with Application Structure
- Section 3: Building an Analytical Application
- Further reading
- Sample questions
- Summary
- Dropping unwanted tables immediately after use
- Optimized load
- Non-optimized load
- Optimized QVD load
- Reducing the size of data as much as possible
- Applymap()
- Using Applymap instead of joins
- Script optimization
- As-Of Table
- Canonical dates
- Link table
- Why use QVDs?
- QVDs
- Filtering data in the script editor
- Filtering data using the Data manager
- Filtering
- The NoConcatenate
- Forced concatenation
- Automatic concatenation
- Concatenation
- Pitfalls of using joins
- Inner join
- Right join
- Left join
- Join/outer join
- Types of joins
- Joining
- Dimensional modeling
- Entity relationship modeling
- Data modeling techniques
- An overview of data modeling
- Technical requirements
- Implementing Data Modeling Techniques
- Further reading
- Summary
- Profiling using the Data model viewer
- Profiling using the Data manager
- Data profiling
- Table associations
- Data load editor
- Creating calculated fields
- Loading a data file from data files (QlikCloud)
- Loading a data file from a folder (Qlik Sense Desktop)
- Dragging a data file into your application
- Data manager
- Data connections
- Loading data from data sources
- Data loading process
- Technical requirements
- Loading Data in Qlik Sense
- Section 2: Data Loading and Modeling
- Summary
- Self-service with Qlik Sense
- Setting up Qlik Sense Cloud
- Setting up Qlik Sense Desktop
- The Associative Engine
- API and extensibility capabilities
- Objects
- Sheets
- Application overview
- The hub
- Visualization platform
- Data model
- Script
- Data manager
- ETL engine
- In-memory associative database
- The components of Qlik Sense
- An overview of the Qlik Sense product
- Getting Started with Qlik Sense
- Section 1: Qlik Sense and Business Intelligence
- Reviews
- Get in touch
- Conventions used
- Download the color images
- Download the example code files
- To get the most out of this book
- What this book covers
- Who this book is for
- Preface
- Packt is searching for authors like you
- About the reviewer
- About the authors
- Contributors
- Packt.com
- Why subscribe?
- About Packt
- Hands-On Business Intelligence with Qlik Sense
- Copyright and Credits
- Title Page
- coverpage
- coverpage
- Title Page
- Copyright and Credits
- Hands-On Business Intelligence with Qlik Sense
- About Packt
- Why subscribe?
- Packt.com
- Contributors
- About the authors
- About the reviewer
- Packt is searching for authors like you
- Preface
- Who this book is for
- What this book covers
- To get the most out of this book
- Download the example code files
- Download the color images
- Conventions used
- Get in touch
- Reviews
- Section 1: Qlik Sense and Business Intelligence
- Getting Started with Qlik Sense
- An overview of the Qlik Sense product
- The components of Qlik Sense
- In-memory associative database
- ETL engine
- Data manager
- Script
- Data model
- Visualization platform
- The hub
- Application overview
- Sheets
- Objects
- API and extensibility capabilities
- The Associative Engine
- Setting up Qlik Sense Desktop
- Setting up Qlik Sense Cloud
- Self-service with Qlik Sense
- Summary
- Section 2: Data Loading and Modeling
- Loading Data in Qlik Sense
- Technical requirements
- Data loading process
- Loading data from data sources
- Data connections
- Data manager
- Dragging a data file into your application
- Loading a data file from a folder (Qlik Sense Desktop)
- Loading a data file from data files (QlikCloud)
- Creating calculated fields
- Data load editor
- Table associations
- Data profiling
- Profiling using the Data manager
- Profiling using the Data model viewer
- Summary
- Further reading
- Implementing Data Modeling Techniques
- Technical requirements
- An overview of data modeling
- Data modeling techniques
- Entity relationship modeling
- Dimensional modeling
- Joining
- Types of joins
- Join/outer join
- Left join
- Right join
- Inner join
- Pitfalls of using joins
- Concatenation
- Automatic concatenation
- Forced concatenation
- The NoConcatenate
- Filtering
- Filtering data using the Data manager
- Filtering data in the script editor
- QVDs
- Why use QVDs?
- Link table
- Canonical dates
- As-Of Table
- Script optimization
- Using Applymap instead of joins
- Applymap()
- Reducing the size of data as much as possible
- Optimized QVD load
- Non-optimized load
- Optimized load
- Dropping unwanted tables immediately after use
- Summary
- Sample questions
- Further reading
- Section 3: Building an Analytical Application
- Working with Application Structure
- Technical requirements
- Application overview
- Toolbars
- Understanding the DAR methodology
- Creating visualization objects
- Getting started
- Generating visualizations using Insights Advisor
- Generating visualizations using Insights Advisor for selected fields
- Creating visualizations using chart suggestions
- Creating visualizations manually
- Creating Master items
- Creating master dimensions
- Creating master measures
- Creating master visualizations
- Calculation expressions
- Summary
- Questions
- Further reading
- Creating a Sales Analysis App Using Qlik Sense
- Technical requirements
- Creating the dashboard sheet
- Creating the dashboard
- Creating a new sheet for the dashboard
- Creating KPI visualizations
- Creating a pie chart with Sales $ by Categories
- Creating a bar chart with Sales $ by Top 10 Customers
- Creating the geographical map of sales by country
- Creating a filter pane with Order Year and Order Month fields
- Creating the analysis sheets
- Creating a customer analysis sheet
- Creating a new sheet for customer analysis
- Adding a filter pane with main dimensions
- Adding KPI visualizations
- Creating a combo chart for Pareto (80/20) analysis
- Creating a table chart with customer information
- Creating a product analysis sheet
- Creating a new sheet for product analysis
- Adding a filter pane
- Adding KPI visualizations
- Creating a bar chart with a drill-down dimension
- Creating a line chart by OrderMonthYear and Category
- Creating a scatter plot
- Creating a reporting sheet
- Creating a new sheet
- Adding a default filter pane
- Summary
- Interacting with Advanced Expressions
- Technical requirements
- Creating calculations with conditions
- Condition to show a text message
- Condition to show a different calculation
- Condition to filter data on a measure
- Using TOTAL for aggregation scope
- Calculating the relative share over the total
- Calculating the relative share over a dimension
- Using some useful inter-record functions
- Calculating sales variance year over year
- Using AGGR for advanced aggregation
- Calculating the top sales product over each category
- Leveraging Set Analysis for in-calculation selection
- Selecting a specific country for comparison
- Summary
- Further reading
- Creating Data Stories
- An overview of stories
- Creating snapshots
- Planning and organizing your presentation
- Creating stories
- Editing your story
- Sharing stories
- Summary
- Further reading
- Section 4: Additional Features
- Engaging On-Demand App Generation
- Technical requirements
- How Qlik Sense handles large volumes of data
- Setting up a Google BigQuery account
- Configuring Qlik Sense for ODAG applications
- Building a summarized application
- Creating a connection
- Adding a script to retrieve data
- Building the detailed application
- Binding expressions in on-demand template apps
- Recovering a long list of selected (or possible) values
- Adding restrictions
- Creating a dynamic SQL
- Integrating the summarized and detailed applications
- Testing our on-demand application
- Summary
- Further reading
- Creating a Native Map Using GeoAnalytics
- Technical requirements
- Concepts of GeoAnalytics
- Creating a map
- Loading geographical data
- Adding the base map
- Adding layers
- Area layer
- Heatmap layer
- Adding more information to the map
- Label
- Info Bubble
- Summary
- Further reading
- Working with Self-Service Analytics
- Technical requirements
- Creating self-service analytics
- Publishing an application
- Creating a new sheet in a published app
- Sharing insights with community sheets
- Approving sheets to add them to a baseline
- Co-creating applications in Qlik Sense Cloud Business
- Managing members
- Editing the application with multiple users
- Sharing the app with users
- Publishing changes to a published application
- Summary
- Further reading
- Data Forecasting Using Advanced Analytics
- Technical requirements
- Qlik Sense Engine and Server Side Extensions
- Qlik approach to data science platforms
- How SSE works
- SSE functions
- Preparing your R environment
- Installing R
- Installing Rserve()
- Installing more packages
- Installing the SSE plugin
- Configuring Qlik Sense
- Qlik Sense Desktop
- Qlik Sense Enterprise
- Starting all services
- Using the R extension in a Qlik Sense application
- Preparing your Python environment
- Installing Python
- Updating Python pip
- Installing TensorFlow
- Using a Python extension
- Configuring Qlik Sense
- Qlik Sense Desktop
- Qlik Sense Enterprise
- Using the Python SSE in your apps
- Summary
- Questions
- Further reading
- Deploying Qlik Sense Apps for Mobile/Tablets
- Technical requirements
- Setting up the Sales Analysis app for mobile usage
- Responsive layouts
- Responsive object design
- Reviewing the responsive design of the Sales Analysis application
- The Quick view sheet
- Choosing the right client
- Preparing the Sales Analysis app for offline usage
- Summary
- Other Books You May Enjoy
- Leave a review - let other readers know what you think 更新時間：2021-07-02 13:06:12
