Qlik Sense interview questions with detailed answers

To create a new app in Qlik Sense, follow these steps:

1. Log in to Qlik Sense and click on the "Create new app" button.
2. Give the app a name and select the appropriate data source.
3. Load data into the app using the "Data load editor" or "Add data" options.
4. Create visualizations using the app's drag-and-drop interface or the Qlik scripting language.

// Example of loading data into a new app using the Data load editor
LOAD
    Product,
    Sales,
    Date
FROM
    SalesData.csv

// Example of creating a bar chart in a new app using the Qlik scripting language
BarChart:
LOAD
    Region,
    Sum(Sales) as Sales
FROM
    SalesData.csv
GROUP BY
    Region;

Once you have created a visualization, you can save it and add it to a dashboard for further analysis and sharing.

In Qlik Sense, a dimension is a categorical variable used to group or categorize data, while a measure is a quantitative variable used to perform mathematical calculations on the data. Dimensions are often used to create visualizations such as tables, bar charts, and pie charts, while measures are used to provide context to these visualizations by summarizing or aggregating the data.

// Example of a dimension in Qlik Sense
LOAD
    Product,
    Sales,
    Date
FROM
    SalesData.csv;

// Example of a measure in Qlik Sense
LOAD
    Region,
    Sum(Sales) as Sales
FROM
    SalesData.csv
GROUP BY
    Region;

In the above examples, "Product" and "Date" are dimensions because they are categorical variables, while "Sales" is a measure because it is a quantitative variable. The second example shows how a measure can be used to summarize the sales data by region.

A data model in Qlik Sense is a way of organizing data to facilitate exploration and analysis. It involves linking different tables of data together based on common fields, which allows users to navigate through the data in a flexible and intuitive way. To create a data model in Qlik Sense, follow these steps:

1. Load the necessary data tables into Qlik Sense using the "Data load editor".
2. Identify common fields between the tables and use the "Join" command to link them together.
3. Use the "Resident" command to create new tables and fields based on the linked data.

// Example of creating a data model in Qlik Sense
SalesData:
LOAD
    SalesID,
    CustomerID,
    ProductID,
    SalesAmount
FROM
    SalesData.csv;

CustomerData:
LOAD
    CustomerID,
    CustomerName,
    City
FROM
    CustomerData.csv;

Join (SalesData)
LOAD
    ProductID,
    ProductName,
    ProductCategory
FROM
    ProductData.csv;

// Create a new table based on the linked data
SalesByCity:
LOAD
    City,
    Sum(SalesAmount) as TotalSales
Resident
    SalesData
Join
    CustomerData
Group By
    City;

In the above example, three tables of data are loaded into Qlik Sense and joined together based on the common field "CustomerID". A new table, "SalesByCity", is then created using the linked data and aggregated by city.

To load data into Qlik Sense, follow these steps:

1. Open Qlik Sense and go to the "Data load editor".
2. Click on the "Add data" button and select the appropriate data source.
3. Choose the data tables or files to load into Qlik Sense and configure any necessary settings such as field delimiters and data types.
4. Use the Qlik scripting language to transform and manipulate the data as needed.

// Example of loading data into Qlik Sense from a CSV file
LOAD
    Product,
    Sales,
    Date
FROM
    SalesData.csv;

// Example of loading data into Qlik Sense from a database
LIB CONNECT TO 'MyDatabase';

LOAD
    CustomerName,
    OrderDate,
    OrderAmount
FROM
    MyDatabase.dbo.Orders;

In the above examples, data is loaded into Qlik Sense from a CSV file and a database using the "LOAD" command in the Qlik scripting language. The "FROM" clause specifies the data source, while the fields to be loaded are listed in the "LOAD" clause.

In Qlik Sense, a visualization is a graphical representation of data that helps users to better understand and explore their data. Qlik Sense provides a wide range of visualization options such as bar charts, line charts, scatter plots, and more. To create a visualization in Qlik Sense, follow these steps:

1. Select the appropriate data model and open the "Sheet" view.
2. Click on the "Visualizations" button and select the desired visualization type.
3. Choose the relevant fields to be displayed in the visualization.
4. Customize the visualization as needed using the formatting options.

// Example of creating a bar chart visualization in Qlik Sense
Chart:
LOAD
    ProductCategory,
    Sum(SalesAmount) as TotalSales
FROM
    SalesData
GROUP BY
    ProductCategory;

// Open the Sheet view and click on "Bar chart" under "Visualizations"
// Choose "ProductCategory" for the dimension and "TotalSales" for the measure
// Customize the chart as needed using the formatting options

In the above example, a bar chart visualization is created in Qlik Sense using the "ProductCategory" field as the dimension and the "TotalSales" field as the measure. The resulting chart shows the total sales for each product category.

A master item in Qlik Sense is a reusable object that can be used across multiple visualizations and apps. It can be a dimension, measure, visualization, or other object that has been saved as a master item for easy reuse. To create a master item in Qlik Sense, follow these steps:

1. Create the desired object (dimension, measure, visualization, etc.) in the app.
2. Right-click on the object and select "Add to master items".
3. Give the master item a name and choose any additional settings or properties.
4. Save the master item for reuse in other visualizations or apps.

// Example of creating a master item in Qlik Sense
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
FROM
    SalesData.csv;

// Create a measure for total sales
TotalSales:
Load
    Sum(SalesAmount) as TotalSales
Resident
    SalesData;

// Save the measure as a master item for reuse
TotalSalesMasterItem:
Load
    'TotalSales' as MasterItemName,
    *
Resident
    TotalSales;

In the above example, a master item is created for the "TotalSales" measure in Qlik Sense. The measure is first created using the "Sum" function and then saved as a master item using the "Load" and "Resident" commands. The resulting master item can be easily reused in other visualizations or apps.

To create a filter pane in Qlik Sense, follow these steps:

1. Open the sheet view in Qlik Sense.
2. Click on the "Filters" button and select "Filter pane".
3. Choose the desired fields to be displayed in the filter pane.
4. Customize the filter pane as needed using the formatting options.

// Example of creating a filter pane in Qlik Sense
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
FROM
    SalesData.csv;

// Open the Sheet view and click on "Filters" under "Visualizations"
// Choose the desired fields to be displayed in the filter pane
// Customize the filter pane as needed using the formatting options

In the above example, a filter pane is created in Qlik Sense using the "SalesData" table. The resulting filter pane can be used to filter the data by various fields such as "OrderDate", "CustomerName", or "ProductName".

A line chart in Qlik Sense is a type of chart that displays data points connected by lines. It is typically used to show trends or changes over time. A bar chart in Qlik Sense, on the other hand, is a type of chart that uses horizontal or vertical bars to represent data. It is typically used to compare values across categories.

// Example of a line chart in Qlik Sense
LineChart:
LOAD
    Date,
    SalesAmount
FROM
    SalesData.csv;

// Create a line chart with Date as the X-axis and SalesAmount as the Y-axis
LineChart:
LOAD
    Date,
    Sum(SalesAmount) as SalesAmount
Resident
    SalesData
Group By
    Date;

// Example of a bar chart in Qlik Sense
BarChart:
LOAD
    ProductName,
    SalesAmount
FROM
    SalesData.csv;

// Create a bar chart with ProductName as the X-axis and SalesAmount as the Y-axis
BarChart:
LOAD
    ProductName,
    Sum(SalesAmount) as SalesAmount
Resident
    SalesData
Group By
    ProductName;

In the above examples, a line chart is created using the "Date" field as the X-axis and "SalesAmount" as the Y-axis. This line chart can be used to show trends or changes in sales over time. A bar chart, on the other hand, is created using the "ProductName" field as the X-axis and "SalesAmount" as the Y-axis. This bar chart can be used to compare sales across different products.

To create a calculated field in Qlik Sense, follow these steps:

1. Open the script editor in Qlik Sense.
2. Use the LOAD statement to load the relevant data from the data source.
3. Use the AS keyword to create a new field with the calculated value.

// Example of creating a calculated field in Qlik Sense
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
FROM
    SalesData.csv;

// Create a new field called "Profit" by subtracting "Cost" from "SalesAmount"
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount,
    (SalesAmount - Cost) AS Profit
FROM
    SalesData.csv;

In the above example, a new calculated field called "Profit" is created in Qlik Sense by subtracting the "Cost" field from the "SalesAmount" field in the "SalesData" table. This new field can be used in visualizations and analysis like any other field.

In Qlik Sense, a bookmark is a saved view of a particular sheet, visualization, or state of selections. It allows users to quickly return to a particular view or analysis at a later time without having to manually recreate it. To create a bookmark in Qlik Sense, follow these steps:

1. Open the sheet or visualization that you want to bookmark.
2. Make any selections or filters that you want to save.
3. Click the "Bookmark" button in the toolbar.
4. Enter a name for the bookmark and click "Save".

// Example of creating a bookmark in Qlik Sense
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
FROM
    SalesData.csv;

// Create a new sheet called "Sales Analysis"
Sales Analysis:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
Resident
    SalesData;

// Make some selections and filters on the "Sales Analysis" sheet
// Click the "Bookmark" button and enter a name for the bookmark
// The bookmark is now saved and can be accessed later

In the above example, a new sheet called "Sales Analysis" is created in Qlik Sense and some selections and filters are made. The user can then click the "Bookmark" button and enter a name for the bookmark to save this view for future use.

To create a story in Qlik Sense, follow these steps:

1. Open the Qlik Sense app.
2. Click on the "Stories" button in the toolbar.
3. Click on the "Create new story" button.
4. Add sheets, visualizations, and media to the story by clicking the "Add slide" button.
5. Customize the layout, theme, and style of the story using the formatting options.
6. Save the story by clicking the "Save" button.

// Example of creating a story in Qlik Sense
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
FROM
    SalesData.csv;

// Create a new sheet called "Sales Analysis"
Sales Analysis:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
Resident
    SalesData;

// Click the "Stories" button in the toolbar
// Click the "Create new story" button and add slides
// Customize the layout, theme, and style of the story
// Save the story by clicking the "Save" button

In the above example, a new sheet called "Sales Analysis" is created in Qlik Sense, and a story is created by adding the sheet to a new slide and customizing the layout and theme of the story. Once the story is complete, it can be saved and shared with other users.

In Qlik Sense, a connection is a link to an external data source that enables you to load data into your Qlik Sense app. You can create a connection in Qlik Sense by following these steps:

1. Open the Qlik Sense Hub.
2. Click on "Create new app" or open an existing app.
3. Click on "Add data" and select the data source type you want to connect to.
4. Enter the required information for the data source, such as server name, database name, username, and password.
5. Test the connection to ensure that it is working properly.
6. Save the connection and use it to load data into your Qlik Sense app.

// Example of creating a connection to a SQL Server database in Qlik Sense
LIB CONNECT TO 'SQL Server Connection';

// Load data from the database using the connection
SalesData:
LOAD
    OrderDate,
    CustomerName,
    ProductName,
    SalesAmount
FROM
    [dbo].[Sales]
WHERE
    Year(OrderDate) = 2022;

In the above example, a connection to a SQL Server database is created using the "LIB CONNECT" statement, and data is loaded from the "Sales" table into the "SalesData" table using the connection. Once the connection is established, you can use it to load data from the data source into your Qlik Sense app.

In Qlik Sense, you can create a pivot table by following these steps:

1. Open a Qlik Sense app and navigate to the sheet where you want to create the pivot table.
2. Click on "Add object" and select "Pivot table" from the list of available chart types.
3. Drag and drop the dimensions and measures you want to use into the appropriate areas of the pivot table.
4. Customize the appearance and behavior of the pivot table using the "Properties" panel.

// Example of creating a pivot table in Qlik Sense
PivotTable:
PivotTable
LOAD
    Year,
    Month,
    CustomerName,
    ProductName,
    Sum(SalesAmount) as TotalSales
FROM
    [lib://SalesData.qvd]
GROUP BY
    Year,
    Month,
    CustomerName,
    ProductName;

// Display the pivot table on a Qlik Sense sheet
PivotTable:
LOAD * INLINE [
    Year, Month, CustomerName, ProductName, TotalSales
    2022, Jan, Customer A, Product X, 500
    2022, Jan, Customer A, Product Y, 750
    2022, Jan, Customer B, Product X, 250
    2022, Jan, Customer B, Product Y, 1000
];

In the above example, data is loaded from a QVD file into a pivot table using the "LOAD" statement. The dimensions used in the pivot table are "Year", "Month", "CustomerName", and "ProductName", while the measure is "TotalSales". The pivot table is then displayed on a Qlik Sense sheet using the "PivotTable" chart object.

In Qlik Sense, a join is used to combine data from two or more tables based on a common field. You can perform a join using the "JOIN" or "LEFT JOIN" statements in the script editor. Here's an example:

// Example of a join in Qlik Sense
Sales:
LOAD
    SalesID,
    SalesDate,
    ProductID,
    CustomerID,
    SalesAmount
FROM
    [lib://SalesData.qvd];

Products:
LOAD
    ProductID,
    ProductName
FROM
    [lib://ProductData.qvd];

// Join the Sales and Products tables based on the ProductID field
SalesJoinProducts:
JOIN (Sales)
LOAD
    ProductID,
    ProductName
RESIDENT
    Products;

// Display the joined table on a Qlik Sense sheet
SalesJoinProducts:
LOAD * INLINE [
    SalesID, SalesDate, ProductID, CustomerID, SalesAmount, ProductName
    1, 2022-01-01, 100, 1, 500, Product X
    2, 2022-01-01, 101, 2, 750, Product Y
    3, 2022-01-02, 102, 3, 250, Product Z
];

In the above example, two tables ("Sales" and "Products") are loaded from QVD files. A join is performed between these tables based on the "ProductID" field using the "JOIN" statement. The resulting table ("SalesJoinProducts") includes all fields from the "Sales" table, as well as the "ProductName" field from the "Products" table. The joined table is then displayed on a Qlik Sense sheet using the "SalesJoinProducts" table.

In Qlik Sense, a filter is used to restrict data based on specific values or conditions, while a search box is used to find data based on keywords or phrases. Filters can be applied to individual visualizations or to an entire sheet, while search boxes are typically used to search across multiple visualizations on a sheet.

To apply a filter, you can either use the filter pane or create a filter object on a visualization. For example:

// Create a filter object on a bar chart visualization
Chart:
LOAD
    SalesPerson,
    SalesAmount
FROM
    [lib://SalesData.qvd]
WHERE
    SalesDate >= '2022-01-01';

BarChart:
LOAD
    SalesPerson,
    Sum(SalesAmount) as TotalSales
RESIDENT
    Chart
GROUP BY
    SalesPerson;

// Create a filter object on the BarChart visualization
BarChartFilter:
LOAD
    SalesPerson
RESIDENT
    Chart
GROUP BY
    SalesPerson;

// Display the bar chart visualization with a filter object
BarChart:
LOAD * INLINE [
    SalesPerson, TotalSales
    John Smith, 5000
    Jane Doe, 7500
    Bob Johnson, 2500
];

// Add a filter object to the BarChart visualization
BarChartFilter:
LOAD * INLINE [
    SalesPerson
    John Smith
];

In the above example, a bar chart visualization is created showing the total sales by salesperson. A filter object is also created based on the "SalesPerson" field. The resulting bar chart visualization is displayed along with the filter object, which will restrict the data shown in the chart based on the selected salesperson.

To use a search box, you can add a search object to a sheet and then configure it to search across one or more visualizations. For example:

// Add a search object to a sheet
SearchObject:
LOAD
    SalesPerson,
    SalesAmount
FROM
    [lib://SalesData.qvd]
WHERE
    SalesDate >= '2022-01-01';

// Configure the search object to search across the SalesPerson and SalesAmount fields
SearchObjectProperties:
LOAD
    'SalesPerson,SalesAmount' as SearchFields,
    'Contains' as MatchMode
RESIDENT
    SearchObject;

// Display the search object on the sheet
SearchObject:
LOAD * INLINE [
    SalesPerson, SalesAmount
    John Smith, 5000
    Jane Doe, 7500
    Bob Johnson, 2500
];

In the above example, a search object is added to the sheet and configured to search across the "SalesPerson" and "SalesAmount" fields using a "Contains" match mode. The resulting search object is displayed on the sheet and can be used to find data based on keywords or phrases.

The data model viewer in Qlik Sense allows you to visualize the data model and relationships between tables in your app. It provides an overview of the data structure and helps identify potential issues, such as circular references. You can access the data model viewer by navigating to the "Data Model Viewer" in the "App Overview" menu. Once there, you can explore the tables, fields, and relationships in your data model, and make any necessary changes. Here's an example of how to access the data model viewer:

1. Open your Qlik Sense app
2. Click on the "App Overview" button in the top left corner
3. Select "Data Model Viewer" from the dropdown menu
4. Explore the tables, fields, and relationships in your data model

To create a histogram chart in Qlik Sense, you can use the "Histogram" chart type under "Basic Types" in the "Charts" pane. You will need to select the dimension and measure that you want to use to create the chart. A histogram chart can help you understand the distribution of your data by showing the frequency of values in specific ranges or bins. With a histogram chart, you can identify patterns or outliers in your data that may not be visible with other chart types. Here's an example of how to create a histogram chart in Qlik Sense:

1. Open your Qlik Sense app
2. Click on the "Edit" button in the top right corner
3. Drag and drop the "Histogram" chart type from the "Charts" pane
4. Select the dimension and measure you want to use
5. Adjust the settings as necessary, such as the number of bins or the range of values to display
6. Preview and save your chart

To implement drill-through in Qlik Sense, you can create a drill-through action that links a chart or table to another sheet or dashboard in your app. This allows users to drill down into specific data points to get more detailed information. Benefits of drill-through include increased interactivity and the ability to provide more targeted insights to users. Here's an example of how to create a drill-through action in Qlik Sense:

1. Open your Qlik Sense app
2. Click on the chart or table that you want to add the drill-through to
3. Go to "Selections" in the "Visualizations" pane
4. Click on "Add" under "Drill actions"
5. Choose the target sheet or dashboard that you want to link to
6. Select the fields that you want to use for the drill-through
7. Preview and save your drill-through action

Once you have created the drill-through action, users can right-click on a data point in the chart or table and select "Drill Through" to navigate to the linked sheet or dashboard.

A KPI, or Key Performance Indicator, is a visual representation of a specific metric that measures the performance of a business process. In Qlik Sense, a KPI can be created by using the KPI object. You can specify a dimension and a measure, as well as define the color and appearance of the KPI. Here's an example of creating a KPI that shows the sum of sales:

KPI Object:
Dimension: Product
Measure: Sum(Sales)

Once created, the KPI can be added to a sheet and can provide a quick and easy way to monitor important metrics for your business.

The expression editor in Qlik Sense is used to create complex calculations and expressions. To open the expression editor, click on the "+" sign next to the dimensions or measures in the chart properties. Once in the expression editor, use mathematical operators and functions to create your desired expression.

For example, to calculate the average sales for each month, you can use the following expression:

Avg(Sales)

To calculate the total sales for a particular year, you can use the following expression:

Sum({<Year={2019}>} Sales)

The expression editor also includes a function library that provides pre-built functions to use in your expressions.

A distribution plot in Qlik Sense is a type of chart that displays the distribution of a dataset. It can be used to analyze the spread of values, their central tendency, and identify potential outliers. In Qlik Sense, you can create a distribution plot using the "Distribution Plot" visualization object. To use it, you need to select a field from your dataset, and the distribution plot will automatically calculate and display the distribution of data for that field. You can also customize the appearance and behavior of the chart using the properties panel.

To create a funnel analysis in Qlik Sense, you can use a combination of a bar chart and a calculated dimension. The calculated dimension can be used to group the data by stages of the funnel, and the bar chart can display the counts or percentages of records at each stage. By analyzing the funnel, you can identify the drop-off rates at each stage, and take action to improve the conversion rates. For example, you can identify which stages have the highest drop-off rates and focus on improving the user experience or addressing pain points. Below is an example of a funnel chart expression:

Count({<Stage={'Lead', 'Opportunity', 'Quote', 'Closed Won'}>} Distinct CustomerID)

This expression counts the number of unique customer IDs at each stage of the funnel.

The dimension limits feature in Qlik Sense limits the number of dimension values displayed in a chart based on a set condition, allowing users to focus on top or bottom values. This can be useful when dealing with a large number of dimension values, where only a few values are of interest. To use this feature, simply click on the dimension in the chart, select "Dimension Limits," and set the condition. For example, to show only the top 10 values, set the "Show" option to "Top" and the "Limit" to 10.

A scatter plot in Qlik Sense is used to plot two-dimensional data points where each point represents a value for two different measures. A bubble chart is similar to a scatter plot, but it adds a third dimension, which is represented by the size of the bubbles. The size of each bubble is proportional to the value of a third measure.

To create a scatter plot or a bubble chart, you need to select two measures for the scatter plot and three measures for the bubble chart. You can use the following code snippets to create them:

// Scatter plot
ScatterPlotChart:
LOAD Sales, Profit
FROM Sales.csv
(ooxml, embedded labels, table is Sheet1);

// Bubble chart
BubbleChart:
LOAD Sales, Profit, Discount
FROM Sales.csv
(ooxml, embedded labels, table is Sheet1);

You can then use these measures in the visualization to create the scatter plot or bubble chart.

There are several ways to optimize the performance of a Qlik Sense app:

• Load only necessary data and avoid loading unnecessary fields or tables
• Use optimized data model design such as star schema
• Optimize expressions by avoiding complex calculations and using pre-calculated fields or summary tables
• Use binary load or QVDs to reduce reload time
• Use section access to restrict data access
• Use Qlik Sense Enterprise for better scalability and performance.

In Qlik Sense, a data island is a table that is not linked to the main data model. It is used to store and manage data that is not available in the main data model. Data islands are often used to hold data that is not available in the data source, such as static or reference data. They can also be used to improve the performance of complex calculations by pre-calculating and storing the results in the data island. To create a data island, simply create a new table and load the data into it using the LOAD statement.

Section access is used to restrict access to specific data or parts of an app in Qlik Sense. It involves creating a section access table in the data model with fields for user ID, password, and access permissions. The section access table is then linked to the main data model with a script command, and access is granted or denied based on the user's credentials.

Here's an example of a section access table and how to link it to the data model:

Section Access;
LOAD * INLINE [    ACCESS, USERID, PASSWORD, GROUP    ADMIN, admin, admin123, AdminGroup    USER, user1, user123, UserGroup];

Section Application;

// rest of the script goes here

In this example, the section access table has two users with different access permissions, and their credentials are linked to specific user groups. The Section Application command indicates the start of the main data model script. With this setup, only users with the correct credentials and group permissions will be able to access the app and its data.

Dimension drill-down in Qlik Sense is a feature that allows users to explore data hierarchies by drilling down from one level of detail to a lower level of detail. This is useful for analyzing data at different levels of granularity, such as exploring sales data by product category and then by individual product. To set up a dimension drill-down in Qlik Sense, you can create a hierarchy in your data model by linking related fields, and then configure the visualization to allow for drill-down interactions. This can be done using the "Drill-down groups" section in the visualization's properties panel.

Set analysis is a powerful feature in Qlik Sense that enables you to perform advanced calculations and analysis based on a specific set of data. With set analysis, you can define a set of data based on a specific condition or set of conditions, and then perform calculations based on that set of data.

For example, you can use set analysis to calculate the total sales for a specific product category, or for a specific time period. The syntax for set analysis includes the use of square brackets, and can be used within expressions to filter data based on specific conditions.

Sum({<ProductCategory={'Office Supplies'}>} SalesAmount)

In this example, the expression calculates the sum of sales amount for the product category "Office Supplies".

In Qlik Sense, a dynamic title can be created using expressions in the title section of a sheet or visualization. To create a dynamic title, click on the "Title" section of the sheet or visualization and then select "Custom". Enter an expression in the "Title" field that will update the title based on selected filters or other conditions. For example, the following expression will display the count of selected values in a field called "Product":

=Count({<Product=>} Product)

This will display the count of selected products in the title, and update dynamically as the selection changes.

In Qlik Sense, a container is a sheet object that allows you to group and organize other sheet objects, such as charts, tables, and text boxes. You can use a container to create more complex layouts and enable advanced interactivity. For example, you can set up a container to change the contents or position of its child objects based on user selections. To create a container, click on "Add object" from the sheet toolbar and select "Container". You can then drag and drop other sheet objects into the container and configure its properties.

To create a mashup in Qlik Sense, you need to use web technologies such as HTML, CSS, and JavaScript, along with Qlik Sense APIs. You can use the Qlik Sense Dev Hub to create a new mashup project and then add your visualizations and custom code to the project. You can also use extensions, which are pre-built mashup components that you can add to your app. Here is an example of adding an extension to a mashup:

<div id="myExtension"></div>

<script>
  require(["js/qlik"], function(qlik) {
    qlik.registerExtension('myExtension', function() {
      return {
        paint: function($element, layout) {
          // Add custom code to render extension
        }
      };
    });
  });
</script>

A QVD (QlikView Data) file is a file format used for optimized data storage and retrieval in Qlik Sense. It allows for faster data processing and reduces the load on the source system. To create a QVD file in Qlik Sense, you can use the 'STORE' statement in the script editor, like this:

// Load data from a source
MyData:
LOAD *
FROM [lib://MySource/MyData.qvd];

// Transform and filter the data

// Store the transformed data as a QVD file
STORE MyData INTO [lib://MyQVD/MyData.qvd];

This will save the 'MyData' table as a QVD file in the 'MyQVD' library. You can then load this QVD file into other apps using the 'LOAD' statement.

To create a waterfall chart in Qlik Sense, follow these steps:

1. Load your data into Qlik Sense.
2. Create a new sheet and add a chart to it.
3. Select the "Waterfall" chart type from the "Chart Types" tab in the chart properties.
4. Drag and drop the dimensions and measures you want to display in the chart.
5. Customize the appearance of the chart using the "Appearance" and "Data" tabs in the chart properties.

Here's an example of how to create a simple waterfall chart using the sample data provided in Qlik Sense:

Chart Properties:
  Chart Type: Waterfall
  Dimensions:
    Category
  Measures:
    Start Value
    Change Value
  Appearance:
    Set colors for positive and negative values

A waterfall chart is useful for visualizing how values change over time or across different categories, and can help identify the most significant positive and negative contributors to a net change.

Alternate states in Qlik Sense allow for the creation of multiple selections states within the same visualization, allowing for advanced comparative analysis. To implement alternate states, you need to use the Alternate States feature in the Qlik Sense visualization settings. Then, you can use the State function in your expressions to specify which state you want to use. For example:

sum({<Year = {$(=max(Year))}>} Sales) // Uses default state
sum({<Year = {$(=max(Year))}>} State2 Sales) // Uses alternate state named "State2"

This expression will only calculate sales for the maximum year in the default state and for the maximum year in the "State2" alternate state.

To create a heat map in Qlik Sense, you can use a scatter plot chart and configure it to use colors based on data density. Here's an example expression to calculate the density:

=Log10(Count(FieldName))/Log10(Max(Count(FieldName)))

Then, go to the "Data" tab, select the scatter plot chart, and add your dimensions and measures. Under the "Appearance" tab, go to the "Color" section and choose "By Expression". Enter the density expression in the "Expression" field and select a color scale. The resulting chart will show a heatmap of the data density.

A geo-analytics map in Qlik Sense is a map chart that displays data points based on their geographic location. It provides the ability to explore data geospatially and uncover location-based insights. To create a geo-analytics map in Qlik Sense, you need to have a data set that includes location data, such as latitude and longitude. You can then add the location field to the map chart and use the expression editor to define the size and color of the data points. Example code snippet:

Map:
LOAD *,
     Latitude,
     Longitude,
     Sales
FROM Data.csv
( txt, codepage is 1252, embedded labels, delimiter is ',', msq);

MapChart:
LOAD *,
     GeoMakePoint(Latitude, Longitude) as GeoPoint
Resident Map;

MapChart:
MAP
Latitude, Longitude,
SUM(Sales)
FROM Map
GROUP BY Latitude, Longitude;

To create a funnel chart in Qlik Sense, follow these steps:

1. Load the data into Qlik Sense.
2. Open a new sheet and add a bar chart.
3. In the chart properties panel, go to the "Data" tab and set the dimension to the funnel stages.
4. Set the measure to the value you want to measure at each stage.
5. Go to the "Sort" tab and sort the dimension in the correct order for the funnel.
6. Customize the chart's appearance as desired.

In Qlik Sense, a synthetic key occurs when two or more tables are joined by two or more fields with the same name. This can result in unwanted duplication of data and poor application performance. To avoid synthetic keys, rename the fields in one of the tables to make them unique, or use the Qualify statement to add a table prefix to all field names. Here's an example of using the Qualify statement to avoid synthetic keys:

Qualify *;
Table1:
LOAD A, B, C
FROM ...
Table2:
LOAD D, E, F
FROM ...
Unqualify *;

In the example above, the Qualify statement adds a prefix to all field names in both tables, and the Unqualify statement removes the prefix after the data is loaded. This avoids any potential synthetic keys between the two tables.

In Qlik Sense, you can use the Set Analysis Wizard to create complex set expressions. To use the wizard, click on the "Set Analysis" button in the expression editor, and select "Set Analysis Wizard." From there, you can select the fields and operators to create your set expression. The wizard will generate the set expression for you, which you can then copy and paste into your expression. Here's an example:

Sum({<Year={"$(=Max(Year))"}, Region={'North'}, Category={'Furniture'}>} Sales)

This expression sums up the sales for the current year, in the North region, for the Furniture category. The set expression is enclosed in curly braces and uses the "<" and ">" symbols to define the selection criteria.

A master dimension in Qlik Sense is a reusable dimension that can be applied to multiple visualizations. It allows for consistent formatting and filtering across the entire app. To create a master dimension, go to the "Master items" section of the Qlik Sense hub, click "Create new item," and select "Dimension." Then, enter the dimension's properties and save it. Once created, the master dimension can be used in any visualization by selecting it from the dimensions list. For example:

Dimension: MasterDimension
Field: CustomerName
Expression: Sum(Sales)

Then, the "MasterDimension" can be used in multiple visualizations within the app.

A multi-chart in Qlik Sense allows you to combine multiple visualizations in a single object, providing a more comprehensive analysis of your data. To create a multi-chart, simply drag and drop the desired charts onto a sheet, and then use the "Group" option to combine them. Benefits of using multi-charts include saving space on a sheet, reducing clutter, and allowing for easier comparison between different charts. Here's an example of creating a multi-chart by grouping a bar chart and a line chart:

1. Drag and drop a bar chart and a line chart onto a sheet.
2. Select both charts by holding down the Ctrl key and clicking on each chart.
3. Right-click on one of the charts and select "Group".
4. Customize the appearance and settings of the multi-chart as desired.

To use the map chart in Qlik Sense, you need to load data with geospatial information, such as latitude and longitude coordinates or a location name that can be geocoded. Once you have the data, you can create a map chart by selecting the appropriate chart type in the Qlik Sense interface and setting the relevant dimensions and measures. You can also customize the map style and add layers, such as boundaries or point data. The map chart is useful for visualizing geographic trends and patterns in your data, such as sales by region or customer location.

Here is an example of creating a simple map chart in Qlik Sense using sample data:

1. Load data with geospatial information
2. Select the "Map" chart type in the Qlik Sense interface
3. Set the dimension to the location field, such as City or Country
4. Set the measure to the metric you want to display, such as Sales or Population
5. Customize the map style and add layers, such as boundaries or point data
6. Analyze the map chart to gain insights into your geospatial data

In Qlik Sense, an app object is a visual representation of data that is created within a Qlik Sense app. Examples of app objects include charts, tables, and KPIs. To create an app object, first create a visualization within the app, then choose the object type and customize it using the object properties. Here's an example of creating a bar chart object in Qlik Sense:

1. Select a dataset within the app.
2. Click "Create New Sheet" to create a new sheet.
3. Click "Add" to add a new object.
4. Choose "Bar Chart" as the object type.
5. Customize the chart properties, including dimensions and measures, chart type, and appearance.
6. Save the object to the sheet.

To design a Qlik Sense app that can handle large datasets, you can follow these best practices:

• Load only the necessary data using a QVD file or incremental load.
• Optimize data model by using proper data modeling techniques, such as data reduction, and reducing synthetic keys.
• Use efficient expressions and avoid complex calculations.
• Limit the number of visualizations and use the ones that are appropriate for the data.
• Use data compression techniques to reduce memory consumption.
• Optimize chart performance by setting proper properties such as chart size, limit data points, and reducing transparency.

Incremental loading is a technique used to load large amounts of data into Qlik Sense in a more efficient way. It involves loading only the data that has changed since the last load instead of reloading the entire dataset. This can significantly reduce the load time and improve app performance.

To implement incremental loading in Qlik Sense, you can use the Qlik Sense data manager or script editor to create a script that identifies the new or updated records and loads them into the app.

Here's an example of a script that uses incremental loading to load new records into an existing Qlik Sense table:

[MyTable]:
LOAD *
FROM [lib://MyDataFolder/MyData.xlsx]
(ooxml, embedded labels, table is MyTable)
WHERE NOT Exists(ID);

This script loads only the records that do not already exist in the table, based on the ID field. You can schedule the script to run at regular intervals to keep the app up to date with the latest data.

Incremental loading is especially useful for large datasets that are updated frequently, as it allows you to maintain real-time data in your Qlik Sense app without the need to reload the entire dataset each time.

To create a custom connector in Qlik Sense, you would use the Qlik Web Connectors tool. This tool allows you to connect to various data sources, create custom connectors, and integrate them with Qlik Sense.

To create a custom connector, you need to define the connection properties, authentication method, and REST endpoints. You can then use the connector in Qlik Sense to fetch data from the data source.

Here is an example of creating a custom connector in Qlik Web Connectors:

// Define connection properties
ConnectionProperties:
LOAD * INLINE [
    Name, Value
    Endpoint, https://api.example.com
    Timeout, 60
];

// Define authentication method
Authentication:
LOAD * INLINE [
    Method, ApiKey
    ApiKey, ABC123
];

// Define REST endpoints
RestConnectorMasterTable:
LOAD * INLINE [
    Endpoint, Method, QueryParameters
    /customers, GET, { limit: 100 }
    /orders, GET, { date_range: 'last_month' }
];

// Create custom connector
RestConnector:
REST CONNECT MasterTable (ConnectionProperties)
AUTHENTICATION MasterTable (Authentication)
HTTPHEADER "Content-Type" "application/json"
TablePrefix "custom_"

Once you have created the custom connector, you can use it in Qlik Sense to fetch data from the data source.

The Qlik Sense API allows developers to automate tasks, such as creating or updating apps, managing data connections, and retrieving data. This can be done using various programming languages, including JavaScript and Python. Code snippets can be used to perform tasks such as creating an app, adding data to an app, and reloading data in an app. The API can be accessed through the Qlik Sense Management Console or using the Qlik Sense Desktop API. Comprehensive documentation and examples are available on the Qlik Developer website.

Qlik Sense can be integrated with other BI tools by using different methods such as exporting data from Qlik Sense to other tools or embedding Qlik Sense objects in other BI tools. For example, you can export data from Qlik Sense to Excel, Tableau, or Power BI. You can also embed Qlik Sense objects like charts, tables, and dashboards in other BI tools using Qlik Sense APIs or web integration tools like iframe. Qlik Sense also supports integration with third-party tools like Alteryx, Informatica, and R for data preparation and analysis.

Implementing a data governance strategy in Qlik Sense involves defining policies, procedures, and standards for managing data assets. This includes establishing data quality rules, data lineage, and access controls. The benefits of a data governance strategy include improved data quality, increased trust in data, and better decision-making. Qlik Sense offers built-in data governance features such as data lineage and data profiling to support these efforts. Additionally, it is important to involve stakeholders from different areas of the organization in the development and implementation of the strategy to ensure its success.

In Qlik Sense, a dimension group is a collection of related dimensions that can be easily managed and used in charts and visualizations. To create a dimension group, go to the "Master items" section and click "Dimension group". Then, add the related dimensions to the group and define the group properties. This allows you to easily apply multiple related dimensions to a chart or visualization with a single selection, improving the efficiency of your Qlik Sense app development. Here is an example of creating a dimension group using the Qlik Sense script editor:

DimensionGroups:
LOAD
    Dim1,
    Dim2,
    Dim3
RESIDENT MyTable;

DIMENSION GROUP MyDimensionGroup
(Dim1, Dim2, Dim3);

Qlik Sense Scheduler is used to automate tasks such as data refresh and report generation. To create a task, go to the Qlik Management Console (QMC) and navigate to the "Tasks" section. From there, you can create and schedule tasks to run at specified times. However, the Qlik Sense Scheduler has some limitations, such as a lack of flexibility in scheduling options and limited functionality for complex tasks. For more advanced scheduling options and automation capabilities, users may need to use third-party tools or create custom solutions using the Qlik Sense API.

Qlik Sense data market provides a collection of external data sources that can be integrated into Qlik Sense apps. To use it, go to the Data Load Editor and click on the "Data Market" button. Choose the data source you want to integrate, and follow the prompts to purchase and connect to the data source. Once connected, you can use the data in your app like any other data source. Note that some data sources may require additional authentication or configuration.

The Qlik Sense Hub is the web-based interface used to access Qlik Sense apps, share apps, and collaborate with other users. Users can create their own personalized views of apps and explore data through different sheets and visualizations. To share an app, the user can publish the app to the hub and invite others to access it. The hub also provides a collaborative environment for users to share insights and collaborate on data analysis.

The Qlik Sense visualization API allows developers to create custom visualizations using HTML, CSS, and JavaScript. To create a custom visualization, the developer must first define the properties that can be modified by the user, the data structure that the visualization expects, and the rendering logic. The following code snippet shows an example of how to define the properties of a custom visualization:

define([], function () {
  'use strict';

  return {
    type: 'my-custom-chart',
    component: 'MyCustomChart',
    definition: {
      properties: {
        myProperty: {
          type: 'string',
          ref: 'myProperty',
          label: 'My Property',
          expression: 'optional',
          defaultValue: 'default value'
        }
      }
    }
  };
});

Once the properties are defined, the developer can create the rendering logic using D3.js or any other charting library. The following code snippet shows an example of how to create a simple custom visualization using D3.js:

define(['./d3'], function (d3) {
  'use strict';

  return {
    paint: function ($element, layout) {
      var data = layout.qHyperCube.qDataPages[0].qMatrix.map(function (row) {
        return {
          dimension: row[0].qText,
          measure: row[1].qNum
        };
      });

      var svg = d3.select($element[0]).append('svg')
        .attr('width', $element.width())
        .attr('height', $element.height());

      var bars = svg.selectAll('.bar')
        .data(data)
        .enter()
        .append('rect')
        .attr('class', 'bar')
        .attr('x', 0)
        .attr('y', function (d, i) { return i * 20; })
        .attr('width', function (d) { return d.measure; })
        .attr('height', 20);

      bars.append('text')
        .attr('class', 'label')
        .attr('x', function (d) { return d.measure + 5; })
        .attr('y', function (d, i) { return i * 20 + 15; })
        .text(function (d) { return d.dimension; });
    }
  };
});

Once the custom visualization is defined and implemented, it can be added to a Qlik Sense app using the Qlik Sense dev-hub.

A Qlik Sense Mashup is a web application that integrates Qlik Sense objects into a custom interface, allowing users to interact with the data and visualizations in a tailored environment. To create a mashup, you can use Qlik Sense APIs and web technologies such as HTML, CSS, and JavaScript. Code snippets for creating a simple mashup can be found in the Qlik Sense Dev Hub. The mashup can be embedded on a website or accessed directly via a URL.

A geo-analytics map in Qlik Sense is a visualization that shows data points on a map, allowing users to explore and analyze location-based information. To use it, you need to create a map chart and associate it with a location dimension that contains latitude and longitude data. You can then add additional measures to the chart and customize the appearance of the map. The geo-analytics map is useful for visualizing spatial relationships and identifying patterns in data that are related to location.

To create a funnel chart in Qlik Sense, follow these steps:

1. Add a new sheet to your app.
2. Drag and drop a Funnel chart from the visualization panel onto the sheet.
3. Select the dimension and measures you want to use for the chart.
4. Customize the chart appearance, labels, and colors as needed using the properties panel.

Here's an example code snippet:

// Create a funnel chart
var funnelChart = app.visualization.create('funnel', [
    {
        qDef: {
            qFieldDefs: ['Product Category'],
            qSortCriterias: [{qSortByLoadOrder: 1}]
        }
    },
    {
        qDef: {
            qDef: 'Sum(Sales)',
            qLabel: 'Sales'
        }
    }
], {
    showTitles: true,
    title: 'Sales Funnel by Category'
});

// Add the chart to the sheet
funnelChart.show('chart-container');

A synthetic key is created when two or more tables in Qlik Sense have multiple common fields, resulting in duplicate field names. It can lead to data modeling issues and can cause problems with data aggregation. To avoid a synthetic key, you can rename the common fields in one or more of the tables or concatenate the tables using the appropriate key fields. You can also use a preceding load statement with the "noconcatenate" keyword to create a distinct set of records, thus avoiding synthetic keys. Here is an example of how to rename fields to avoid a synthetic key:

Table1:
LOAD field1,
     field2
FROM [lib://data/Table1.qvd];

Table2:
LOAD field1 as field3,
     field4
FROM [lib://data/Table2.qvd];

In this example, the common field "field1" is renamed as "field3" in Table2 to avoid a synthetic key.

To use the Set Analysis wizard in Qlik Sense:

1. Click on the Set Analysis icon in the Expression Editor.
2. Choose the Set Expression type.
3. Select the dimension(s) you want to filter on.
4. Choose the operator and value(s) for your condition.
5. Add any additional conditions using the "+" button.
6. Click "Generate Set Expression" to generate the set expression code.

For example, the following code calculates the sales amount for products with a price greater than $10:

Sum({$<Price={">10"}>} SalesAmount)

A master dimension in Qlik Sense is a reusable dimension that can be applied to multiple visualizations within a Qlik Sense app. It helps to standardize dimension definitions and reduce the amount of maintenance required when changes are needed. To create a master dimension, you can go to the "Master items" section in the Qlik Sense hub and select "Create new" > "Dimension". You can then define the dimension properties and save it as a master item, which can be used in any visualization within the app.

To create a multi-chart in Qlik Sense, you can use the "Grid" object from the "Layout" section of the "Visualization" pane. You can then drag and drop charts onto the grid, and adjust their size and position as desired.

A multi-chart allows you to display multiple charts in a single view, which can help to provide a more comprehensive picture of the data and allow for easier comparison. It can also help to save space on the sheet, and make the app more user-friendly.

To use the map chart in Qlik Sense, you first need to load geospatial data into your app, either through Qlik GeoAnalytics or by using longitude and latitude coordinates. Once the data is loaded, you can create a map chart by selecting the map chart object and dragging your dimensions and measures onto it. The map chart allows you to visualize your data on a map, providing a powerful way to analyze and understand geospatial patterns and relationships. You can also customize the appearance of the map chart, including the map background, colors, and markers.

In Qlik Sense, an app object is a visual or non-visual item that can be added to a Qlik Sense app, such as a chart, table, or text object. You can create an app object by dragging and dropping it onto the canvas from the "Objects" panel, or by using the "Add New Sheet Object" option in the "Create" menu. You can then customize the object's properties and add data to it using dimensions and measures.