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Introduction to Qlik Sense

Qlik Sense is a modern data analytics platform designed to transform raw data into actionable insights. It leverages Qlik’s unique associative engine, enabling users to explore data relationships without the limitations of traditional queries.

Accessible to both technical users and non-specialists, Qlik Sense provides an intuitive interface that simplifies the creation of interactive dashboards and dynamic visualizations. With its advanced analytics capabilities, the platform supports large and diverse datasets while ensuring optimal performance.

Additionally, Qlik Sense integrates self-service data analytics features, allowing users to ask ad hoc questions and uncover insights in real time. Its connectivity capabilities enable integration with various sources, including on-premise databases, cloud applications, and flat files.

With a flexible and secure architecture, Qlik Sense stands out as a key solution for organizations aiming to democratize data access, enhance decision-making, and foster a data-driven culture.

Getting Started with Qlik Sense

Working with Qlik Sense​

Qlik Sense organizes user activities around key concepts such as apps, streams, and access management. Understanding these fundamentals is crucial to unlocking its full potential.

Qlik Sense Applications​

A Qlik Sense application is the primary container where users develop their analyses. Each application is saved in .qvf format and includes several essential components:

  • Data: Datasets integrated into the application, which can originate from various sources (relational databases, Excel files, APIs, etc.). These data are loaded via the load script.
  • Data model: The relational structure created from the imported data, which Qlik Sense organizes automatically or adjusts as needed.
  • Visualizations: Charts, tables, and other visual elements that translate data into actionable insights.
  • Sheets: Workspaces where users organize their visualizations to analyze data.
  • Custom objects: Extensions or elements added to enhance standard capabilities.

Streams and Workstreams​

Streams in Qlik Sense are secure spaces for grouping and sharing applications with specific user groups. They play a critical role in access and rights management. Key features of streams include:

  • Permission control: Administrators define which users or groups can view, edit, or publish applications in a stream.
  • Application organization: Streams facilitate managing applications by project, department, or other organizational criteria.

A workstream refers to the set of tasks or workflows associated with a stream, including application development, publication within streams, and controlled access for different users.

Access Management​

Qlik Sense uses a role-based access control (RBAC) model to regulate user actions. Standard roles include:

  • Administrators: Full rights over the entire system.
  • Developers: Can create, modify, and publish applications.
  • End users: Can access applications and interact with visualizations based on defined permissions.

Access rights are managed through rules defined in the Qlik Management Console (QMC), allowing granular customization of permissions.

Dimensions and Measures​

In Qlik Sense, dimensions and measures are fundamental concepts for structuring and analyzing data. They transform raw data into actionable visualizations, facilitating decision-making.

Dimensions​

A dimension represents a category or descriptive entity in the data. It defines the axis of analysis and is used to segment or group data. Examples include:

  • Products: Identifying sales by product.
  • Regions: Visualizing performance by geographic area.
  • Periods: Analyzing trends by dates or periods.

Dimensions are directly derived from fields in the data model. In visualizations, they define axes for charts or labels for tables. Key characteristics include:

  • Source: Typically a raw field in a data table, but can also be a calculated dimension (e.g., concatenation of two fields).
  • Role: Dimensions categorize data, enabling granular analyses.
  • Usage: They appear on axes in bar, line, or pie charts.

Measures​

A measure is a calculation or aggregation based on one or more fields in the data model. Measures provide quantitative results, such as:

  • Sums: Total sales.
  • Averages: Average customer ratings.
  • Percentages: Market share by product or region.

Measures are defined using expressions based on Qlik’s language, which includes aggregation functions like Sum(), Avg(), and Count(). Key characteristics include:

  • Source: Often a combination of fields and functions in the data model.
  • Role: Measures synthesize data to provide actionable insights.
  • Usage: Represented numerically, such as bar heights in a bar chart or segment sizes in a pie chart.

Objectives and Interactions​

Dimensions and measures work together to structure visualizations and address analytical questions:

  • Dimensions + Measures: A dimension like "Region" combined with a measure like Sum(Sales) visualizes total sales by region.
  • Comparisons: Users can explore performance across categories by manipulating dimensions.
  • Trends: A time-based dimension associated with an aggregated measure reveals trends in the data.

Importance in Qlik Sense​

Proper use of dimensions and measures maximizes the power of Qlik Sense’s associative engine, enabling rapid and unconstrained data exploration while maintaining precise analytical context. These tools are essential for creating clear, engaging, and actionable visualizations.

Selections and Searches​

The associative approach of Qlik Sense enables smooth and intuitive navigation through complex datasets. Selections and search functions are at the core of this experience, providing powerful tools to explore, filter, and analyze data in real-time.

Selections in Qlik Sense​

Users can make selections directly within visualizations or data fields to explore specific subsets:

  • Direct selection: Click on a value in a dimension (e.g., a region like "Europe") to display associated data.
  • Inclusion and exclusion: Add or exclude selected values by holding the Ctrl key or using contextual options.
  • Navigation between selections: Use the navigation buttons at the top of the interface to return to a previous selection or clear all selections.

Qlik Sense highlights relationships between data:

  • Green: Selected values.
  • White: Values associated with the current selections.
  • Gray: Unassociated values.

Search in Qlik Sense​

Qlik Sense offers multiple search options to quickly locate specific data, even within large datasets:

  1. Global search:
    • Accessible via the search bar at the top of the interface.
    • Allows searching across all fields and visualizations in the application.
    • Supports partial searches: For example, typing "Europ" returns all values containing this string (e.g., "Europe", "European Union").

  2. Search within a specific field:
    • Click on a field in the filter panel or within a visualization.
    • Enter a value or part of a value in the field-specific search bar.
    • Use operators for advanced searches:
    • * to indicate partial matches (e.g., *ope).
    • == for exact matches (e.g., ==Europe).
    • > or < for numerical or chronological searches (e.g., >2020).

  3. Smart search with suggestions:
    • As you type, Qlik Sense provides suggestions based on available data.
    • Results are ranked by relevance according to associative relationships.

  4. Advanced searches within fields:
    • Use logical expressions for complex selections. For example:
    • Select only dimensions where the sum of sales exceeds 1000.
      • =Sum(Sales)>1000
    • Return all regions starting with "A".
      • =Region like 'A*'

  5. Date and range search:
    • Use defined ranges to limit results: e.g.
      • Date >= '2022-01-01' and Date <= '2022-12-31'

Importance of Searches in Analysis​

With these tools, Qlik Sense enables fast and accurate data exploration. The search functions, combined with the associative engine, provide immediate visibility of relevant data, even when the relationships between data are complex or non-linear.

Data Loading​

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Data Load Manager vs. Data Load Editor​

Data Load Manager​

The Data Load Manager is a visual interface integrated into Qlik Sense, designed to simplify data importing and preparation. With its intuitive interface, users can easily connect to various data sources, such as Excel files, relational databases, or cloud services, without writing any code. This tool allows basic transformations, such as renaming columns, selecting fields, or applying simple filters, before loading data into the application.

However, the Data Load Manager has its limitations. It does not support complex transformations, such as incremental loads, conditional data manipulation, or advanced relationships between tables. These limitations make it an ideal tool for beginners or simple projects, but it quickly reaches its limits in scenarios requiring advanced data preparation.

Data Load Editor​

To address more complex needs, Qlik Sense offers the Data Load Editor, a tool designed for technical and advanced users. The Data Load Editor allows scripting in the Qlik scripting language, which offers far greater flexibility and power compared to the Data Load Manager. This language, similar to SQL, uses a simple and intuitive syntax to manipulate data at a more detailed level.

The Data Load Editor enables users to:

  • Perform incremental loads, avoiding the need to reload all data with every update.
  • Create synthetic tables to manage complex relationships or merge data from multiple sources.
  • Clean and transform data in-depth using advanced functions like Join, Concatenate, Group By, or Peek.
  • Manipulate data conditionally, allowing filtering or modifying data based on specific criteria.

Qlik Sense Scripting Language​

The Qlik Sense scripting language is distinguished by its simplicity and similarity to SQL, making it accessible to users with basic data manipulation knowledge. It allows each step of the loading process to be defined precisely, from connecting to data sources to creating the necessary structures for the analytical model. This detailed control ensures optimal performance, even with large or complex datasets.

Additionally, the Qlik scripting language includes tools to detect and correct errors in data, improve data quality, and ensure that the final model perfectly meets the needs of analysis. Thanks to this flexibility, the Data Load Editor is indispensable for complex projects where meticulous data preparation is essential to obtain reliable and actionable insights.

Visualizations​

Visualizations in Qlik Sense​

Qlik Sense is designed to transform raw data into clear and actionable visualizations. The platform offers a complete range of charts and tables suited for different types of analysis, from simple representations to advanced visualizations. Options include bar charts, line charts, pie charts, pivot tables, heat maps, scatter plots, and more. Each visualization type is optimized to present specific data and address particular needs, whether exploring trends, comparing categories, or identifying correlations.

Visualizations can be customized to meet user requirements. This includes modifying colors, scales, data formats, or axes. Such customization ensures that dashboards are not only visually appealing but also relevant and intuitive for decision-making.

Maps and Qlik GeoAnalytics​

Mapping is essential for analyses requiring a geographical dimension. Qlik Sense includes advanced geospatial visualization features through Qlik GeoAnalytics. This tool allows data to be represented on maps, conduct detailed geographic analyses, and interact with spatial information. Features include automatic geocoding, data layer overlays, distance analysis, and clustering.

Qlik GeoAnalytics also supports complex scenarios, such as calculating optimal routes, accessibility analysis, or creating buffer zones. These features address specific needs in fields such as logistics, targeted marketing, or infrastructure management.

Extensions, Qlik Extension Bundles, and Widgets​

Qlik Sense offers extensibility through the use of extensions and widgets. Qlik Extension Bundles are collections of pre-configured visualizations that address specific needs, such as funnel charts or Gantt charts. These extensions extend the native capabilities of the platform without requiring additional development.

For even more personalized needs, users can create or integrate their own extensions using web technologies such as HTML, CSS, and JavaScript. Widgets allow users to customize the appearance and behavior of standard visualizations, providing full control over data presentation.

Enhancing Your Applications​

Color, Order, and Shape​

Optimizing colors, data order, and visual presentation is crucial to ensuring the clarity and impact of dashboards in Qlik Sense. Color choices help prioritize information, draw attention to key points, and make visualizations more accessible. For instance, using consistent palettes to differentiate categories or segments can help clarify complex relationships. Qlik Sense offers advanced options to customize colors based on dimensions, measures, or user-defined thresholds.

Data order also plays a critical role in readability. Users can organize visualizations to highlight the most important information, such as ranking top sales or priority regions. Sorting options in Qlik Sense allow precise control, whether alphabetical, numerical, or based on a specific measure.

Finally, the shape of visualizations, such as the type of chart chosen, should align with the data type and the analysis objective. Qlik Sense offers flexibility to adjust formats, axes, labels, and other elements, ensuring each visualization is optimized for rapid and accurate data interpretation.

Dynamic Calculations and Variables​

Dynamic calculations in Qlik Sense enable displaying results that adapt based on user selections. This makes visualizations interactive and relevant to each analysis context. Dynamic calculations are defined directly within visualization expressions, leveraging advanced functions from the Qlik calculation engine to automatically adjust.

Variables play a key role in simplifying and reusing complex formulas. A variable is a container for a value or expression that can be used across an application. This centralizes the management of calculations, reduces errors, and speeds up application development. For example, a variable can hold a formula for average revenue, used in multiple visualizations without rewriting it each time.

Variables also enable creating interactive parameters, such as adjustable date ranges or thresholds, which users can modify to explore different perspectives. This enhances dashboard interactivity while making the user experience more engaging.

Set Analysis​

Set Analysis is an advanced feature in Qlik Sense that allows aggregations based on specific conditions, independent of current selections. This capability is essential for comparative analysis and complex calculations. For example, Set Analysis can be used to compare current year sales with previous year sales while filtering specific product categories or regions.

The syntax of Set Analysis relies on a clear logical structure that defines a dataset based on conditions. For instance, the expression

Sum({<Year={2022}>} Sales)

calculates the total sales only for the year 2022, regardless of the selections made in the application. This flexibility allows users to go beyond the limitations of current selections and generate more targeted insights.

Set Analysis can also be used for conditional calculations, such as excluding specific values, including only values associated with a given dimension, or comparing distinct segments. Advanced users can leverage this feature to address complex analytical needs while maintaining an interactive and efficient dashboard.

Set Analysis in Qlik Sense allows users to define specific datasets that differ from the current selections made in the dashboard. Unlike standard aggregation, which is based on current selections, Set Analysis enables creating aggregations independent of those selections. This is particularly useful for making comparisons or displaying global metrics, such as the total revenue of a product across all regions, regardless of active selections.

Set Analysis Syntax​

The syntax for Set Analysis is built in several steps:

  1. Define a basic aggregation expression:
    • For example, to calculate total sales:
      • Sum(Sales)
  2. Add a set expression:
    • A set is specified using :
      • Sum({} Sales)
  3. Include a set identifier:

      4. The $ identifier indicates that the Set Analysis takes current selections into account.

      Sum({$} Sales)
  4. Add modifiers:
    • Modifiers allow filtering or redefining the dataset:
    • Total sales in 2023 and 2024:
      • Sum({$<Year={2023,2024}>} Sales)
    • Total sales in Belgium: 
      • Sum({$<Country={'Belgium'}>} Sales)
    • Total sales in North and South America : 
      • Sum({\$<Division={'*America*'}>} Sales)

Additional Operators​

Set Analysis offers several operators to manipulate datasets:

  • Union: combines multiple sets. Example:
    • Sum({\$<Year={'>2022'} + {2019}>} Sales)
  • Exclusion: excludes specific values. This excludes Belgium while considering other selections. Example:
    • Sum({\$<Country-={'Belgium'}>} Sales)
  • Intersection: includes only values common to multiple sets. Example:
    • Sum({\$<Year={'>2020'} * {'<=2022'}>} Sales)
  • Filter removal: ignores selections on a given field. This removes filters on the "Country" field. Example:
    • Sum({\$<Country=>} Sales)

Dynamic Calculations​

Sets can also include dynamically calculated values:

  • Total sales for the maximum year:
    • Sum({\$<Year={\$(=Max(Year))}>} Sales)
  • Total sales for the previous year : 
    • Sum({\$<Year={\$(=Max(Year)-1)}>} Sales)
  • Using variables : 
    • Sum({\$<Year={\$(variable)}>} Sales)

Analyse indirecte​

L’analyse indirecte permet de définir des ensembles basés sur des conditions plus complexes :

  • Total des ventes pour les commandes contenant au moins un produit de la catégorie "Baby Clothes" : 
    • Sum({\$<OrderID=P({1<CategoryName={'Baby Clothes'}>})>} Sales)
  • Exclusion of orders containing products from this category:
    • Sum({\$<OrderID=E({1<CategoryName={'Baby Clothes'}>})>} Sales)

Best Practices​

To simplify the readability and maintenance of complex expressions, it is recommended to:

  • Use variables for frequent or complex definitions.
  • Create Master Items to centralize measures containing Set Analysis.

Easy Creation of a Set Analysis​

A simple method for creating a Set Analysis involves:

  • Making the necessary selections on the dashboard.
  • Opening the expression editor and using the "Set expression" option in the right-hand panel.
  • Ensuring the "Use current selections" option is enabled.
  • Inserting the automatically generated expression.

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Sharing Results​

The ability to effectively share results is essential for maximizing the impact of analyses and fostering collaborative decision-making. Qlik Sense offers specific features to save, organize, and present insights, particularly through bookmarks and the storytelling tool.

Bookmarks​

Bookmarks in Qlik Sense allow saving a specific state of the dashboard. This state includes the selections made, applied filters, and, in some cases, the visual layout of dashboards.

Bookmarks are especially useful for:

  • Quickly navigating to specific analyses: Users can easily return to a particular data configuration without manually reproducing the same selections.
  • Saving time: Automating the recall of frequently used states reduces the time required for recurring analyses.
  • Personalization: Each user can create and manage their own bookmarks based on their specific needs, enhancing the relevance of analyses.
  • Sharing with other users: In some cases, bookmarks can be shared within an organization to standardize analyses or direct users toward key insights.

Storytelling​

The storytelling tool in Qlik Sense is designed to transform interactive analyses into structured narrative presentations. It enables users to capture snapshots of their visualizations and organize them into a logical sequence to present insights.

The main steps of storytelling include:

  • Capturing snapshots: Users select specific visualizations in their dashboard and save them as static snapshots. These snapshots preserve the exact state of the data and selections at the time of their creation.
  • Creating a story: Snapshots are then organized into a narrative timeline, allowing users to tell a coherent story around the data.
  • Adding explanatory content: Users can enhance their presentations with text, annotations, and highlights to guide their audience and clarify key insights.
  • Interacting with the data: While snapshots are static, it is possible to return to the interactive dashboard to explore the underlying data in real time during the presentation.
  • Sharing and collaboration: Created stories can be shared with other members of the organization or exported for external presentations.

The bookmarks and storytelling features of Qlik Sense address specific needs for communication and collaboration. Bookmarks improve efficiency in recurring analyses, while storytelling provides a framework for presenting and explaining complex insights to stakeholders. Together, these tools enhance the impact of data analyses by making results more accessible, understandable, and actionable for everyone in the organization. These features are particularly useful for promoting a data-driven culture and integrating analyses into strategic decision-making processes.

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