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