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The Ultimate Guide for QlikView Interview Questions

Get ready for your QlikView interview with our comprehensive guide on QlikView Interview Questions and Answers. This article covers essential topics and frequently asked questions to help you prepare effectively. Whether you’re a beginner or an experienced professional, you’ll find valuable insights and tips to confidently tackle your QlikView interview and demonstrate your expertise in data visualization and business intelligence.

What is QlikView?

QlikView is a business intelligence (BI) tool used for data visualization and analysis. It allows users to create interactive reports and dashboards to explore and interpret data. QlikView helps organizations make better decisions by providing insights from their data through easy-to-understand visual representations like charts, graphs, and tables. Its user-friendly interface and powerful data processing capabilities enable users to quickly extract meaningful information and identify trends, patterns, and outliers in their data.

Top 30 QlikView Interview Questions and Answers

Q1. Compare QlikView with Tableau?
Ans: QlikView and Tableau are both powerful business intelligence tools, but they have distinct differences:

  • Data Handling:
    • QlikView: Uses an in-memory data model for faster processing and allows for complex data transformations and manipulations directly within the tool.
    • Tableau: Primarily a data visualization tool that excels in creating interactive and beautiful visualizations. Relies more on data prepared outside the tool.
  • User Interface:
    • QlikView: Has a more traditional and somewhat complex user interface, which might have a steeper learning curve for beginners.
    • Tableau: Known for its user-friendly and intuitive drag-and-drop interface.
  • Data Integration:
    • QlikView: Strong ETL (Extract, Transform, Load) capabilities, allowing for complex data integration and transformation.
    • Tableau: Typically requires pre-processed data and relies on external tools for complex data transformations.
  • Performance:
    • QlikView: Highly efficient with large datasets due to its in-memory processing.
    • Tableau: Can handle large datasets well, but may require optimizations for very large data volumes.
  • Deployment:
    • QlikView: Typically deployed as an on-premises solution, though cloud options are available.
    • Tableau: Available both as an on-premises and a cloud-based solution (Tableau Online).

Q2. Explain Set Analysis in QlikView?
Ans: Set Analysis in QlikView is used to define a subset of data that is different from the current selection. It allows users to compare different data sets, make complex aggregations, and enhance analytical capabilities.

Example:

Sum({<Year={2020}, Region={'North America'}>} Sales)

This expression calculates the sum of sales for the year 2020 in the North America region, regardless of the current selections.

Q3. Define Trellis chart?
Ans: A Trellis chart in QlikView is a way of displaying a series of similar charts in a grid layout. It is useful for comparing multiple dimensions or metrics side by side.

Example: If you have sales data for different products across multiple regions, a Trellis chart can display a separate bar chart for each region, making it easier to compare sales performance.

Q4. What is a Pivot table?
Ans: A Pivot table in QlikView allows data to be summarized and viewed from different perspectives. It enables users to dynamically change the data grouping, providing powerful data analysis capabilities.

Example:

  • Rows: Products
  • Columns: Years
  • Values: Sum of Sales

This pivot table layout allows the user to see the total sales for each product by year.

Q5. What is a Straight table?
Ans: A Straight table in QlikView is a tabular representation of data where each row is a record and each column is a field from the data set. Unlike a pivot table, it does not allow dynamic regrouping but provides detailed and straightforward data representation.

Example:

  • Columns: Product, Year, Region, Sales
  • Rows: Individual records

Q6. How many dimensions can you use in a Bar chart?
Ans: In QlikView, a bar chart can typically use up to two dimensions.

Q7. What are Dimensions?
Ans: Dimensions in QlikView are fields used to define how data is grouped in visualizations. They represent categorical data, such as Product, Region, or Year.

Q8. Explain Normalized data?
Ans: Normalized data refers to a database structure where data is organized to minimize redundancy and dependency. This involves structuring the data into multiple related tables to ensure consistency and reduce anomalies.

Q9. Explain the IntervalMatch() function?
Ans: The IntervalMatch() function in QlikView is used to match numeric values to a range of values. It is often used when you need to associate a date or a number with an interval, such as mapping sales data to a time period.

Example:

IntervalMatch(Date)
LOAD StartDate, EndDate
RESIDENT Periods;

This maps the Date field to the appropriate period defined by StartDate and EndDate.

Q10. What do you understand by the extended IntervalMatch() function?
Ans: The extended IntervalMatch() function in QlikView extends the basic IntervalMatch() by allowing additional key fields. It is useful for scenarios where the interval match needs to be performed across multiple dimensions or additional fields.

Example:

IntervalMatch(Date, Product)
LOAD StartDate, EndDate, Product
RESIDENT Periods;

This matches both Date and Product to the corresponding interval and product in the Periods table.

Q11. What are Incremental load and Resident load?
Ans: Incremental load: This is a technique used to load only new or changed data into QlikView, rather than reloading the entire dataset. It improves loading efficiency and performance.

Example:

LOAD * FROM Sales WHERE Date > $(LastLoadedDate);

Resident load: This allows loading data from an already loaded table in QlikView. It is used for transformations or further data manipulation.

Example:

LOAD Product, Sum(Sales) as TotalSales
RESIDENT SalesData
GROUP BY Product;

Q12. What are delimited files and why are they called CSV files?
Ans: Delimited files are text files where each line represents a record, and fields are separated by a specific character (delimiter), such as a comma, tab, or pipe. They are called CSV (Comma-Separated Values) files when the delimiter is a comma.

Example of a CSV file:

Name, Age, Country
John, 30, USA
Jane, 25, UK

Q13. What is Inline data? How can we load Inline into QlikView?
Ans: Inline data refers to data entered directly within the QlikView script. It is useful for adding small, static datasets.

Example of loading Inline data:

LOAD * INLINE [Name, Age, CountryJohn, 30, USAJane, 25, UK];

Q14. What is buffer load, and why is it significant? Ans:
Buffer load in QlikView is a technique to store a local cache of the data to improve loading speed for subsequent reloads. It reduces the need to fetch data from the source repeatedly.

Example:

BUFFER LOAD * FROM SalesData.qvd;

Q15. How many types of charts are used in QlikView?
Ans: QlikView supports various types of charts, including:

  • Bar Chart
  • Line Chart
  • Pie Chart
  • Scatter Chart
  • Combo Chart
  • Gauge Chart
  • Funnel Chart
  • Trellis Chart
  • Block Chart

Q16. What are the parameters needed by a crosstable Wizard to form a cross table?
Ans: The Crosstable Wizard in QlikView requires the following parameters:

  • Qualifier field: The field that remains as is.
  • Attribute field: The field names that will become attribute values.
  • Data field: The actual data corresponding to the attribute values.

Q17. What are the advantages and disadvantages of QlikView?
Ans: Advantages:

  • In-memory processing for fast performance
  • Powerful data integration and transformation capabilities
  • Robust data visualization and analytical features
  • Associative data model for intuitive data exploration

Disadvantages:

  • Steeper learning curve compared to some other tools
  • Less intuitive user interface
  • Higher cost for licensing and deployment

Q18. What is the difference between dimensional and relational modeling?
Ans: Dimensional modeling: Optimized for data warehousing and OLAP cubes, focusing on the ease of querying and reporting. It uses star or snowflake schemas.

Relational modeling: Optimized for transactional databases and follows normalization rules to reduce redundancy. It uses a relational schema.

Q19. What is the difference between the drill-down group (hierarchical groups) and the cyclic group?
Ans: Drill-down group (hierarchical groups): Allows users to navigate from higher to lower levels of data hierarchy (e.g., Year > Quarter > Month).

Cyclic group: Allows users to switch between different dimensions at the same level without hierarchy (e.g., Product Category, Region).

Q20. What are the types of authorization in QlikView?
Ans: QlikView supports several types of authorization:

  • Section Access: Restricting data access at the script level.
  • Document-level security: Permissions set within the QlikView document.
  • Server-level security: Permissions managed by QlikView Server for accessing documents.

Q21. What are the new features in QV 11?
Ans: Some key features introduced in QlikView 11 include:

  • Conditional enabling of objects: Objects can be conditionally displayed.
  • Container objects: Grouping multiple objects into a single container.
  • Improved collaboration features: Sharing insights directly within the platform.
  • Enhanced mobile support: Better usability on mobile devices.

Q22. What is the difference between QVD and QVW?
Ans: QVD (QlikView Data): A file format used for storing data in a highly compressed and optimized way for faster loading.

QVW (QlikView Workbook): The main file format for QlikView documents, which contains the data model, script, and user interface elements.

Q23. What is the difference between QV Publisher and QV Server?
Ans: QlikView Publisher: Manages data reloads, distributions, and automations for QlikView documents. It ensures data is up-to-date and properly distributed.

QlikView Server: Manages user access and delivers QlikView documents to users through a web interface. It handles user sessions and document security.

Q24. What macros are used in your application?
Ans: Macros in QlikView can be used for automating tasks such as exporting data, refreshing data, or performing custom actions. Examples include:

Export to Excel:

Sub ExportToExcel
    set obj = ActiveDocument.GetSheetObject("CH01")
    obj.ExportBiff "C:\Export\Chart.xls"
End Sub

Refresh Data:

Sub RefreshData
    ActiveDocument.Reload
End Sub

Q25. How does QlikView handle data security and what are section access rules?
Ans: QlikView handles data security using Section Access, which controls user access to data at the script level. It allows for row-level security by defining access rights within the script.

Example:

Section Access;
LOAD * INLINE [    ACCESS, USERID, PASSWORD, REDUCTION    ADMIN, admin, admin, *    USER, user1, user1, 1    USER, user2, user2, 2];
Section Application;
LOAD * INLINE [    REDUCTION, Data    1, Sales Data for Region 1    2, Sales Data for Region 2];

This script restricts user1 to see only Region 1 data and user2 to see only Region 2 data.

Q26. What are the primary steps involved in creating a QlikView dashboard?
Ans: Primary steps in creating a QlikView dashboard include:

  • Data Loading: Importing and transforming data from various sources using the script editor.
  • Data Modeling: Creating data relationships and associations.
  • Designing UI: Building the user interface with charts, tables, and other visualization elements.
  • Adding Interactivity: Implementing filters, buttons, and actions for user interaction.
  • Testing: Ensuring the dashboard functions correctly with expected performance.
  • Deployment: Publishing the dashboard to QlikView Server for user access.

Q27. Explain the use of the AGGR() function in QlikView with an example?
Ans: The AGGR() function in QlikView performs aggregation over a specified dimension or set of dimensions. It is used for nested aggregations.

Example: To find the average sales per product category:

Avg(AGGR(Sum(Sales), ProductCategory))

This calculates the sum of sales for each product category and then finds the average of these sums.

Q28. What is the purpose of the ApplyMap() function in QlikView, and how does it differ from a regular join?
Ans: The ApplyMap() function in QlikView is used to map values from one table to another, similar to a lookup operation. It is different from a regular join because it returns a single value based on a key.

Example:

MAP CountryCode USING 'CountryMapping.qvd';
LOAD
    CustomerID,
    ApplyMap('CountryMapping', CountryCode, 'Unknown') as Country
FROM Customers.qvd;

This maps CountryCode to Country using the mapping table and defaults to ‘Unknown’ if no match is found.

Q29. Describe the process of setting up and using alternate states in QlikView?
Ans: Alternate states in QlikView allow users to perform comparative analysis by creating independent sets of selections.

Process:

  1. Create Alternate States: Define alternate states in the Document Properties.
  2. Assign Objects to States: Assign specific charts or objects to different states.
  3. Use States in Expressions: Reference states in set analysis expressions to compare data.

Example: Creating two states (StateA and StateB) and assigning two different charts to these states allows for side-by-side comparison of selections made in each state.

Q30. How can you optimize the performance of a QlikView application?
Ans: Optimizing QlikView performance involves several best practices:

  • Efficient Data Modeling: Avoid synthetic keys and ensure proper data associations.
  • Minimize Data Load: Load only necessary data and use incremental loads.
  • Optimize Expressions: Simplify complex calculations and use efficient functions.
  • Use Aggregations: Pre-aggregate data when possible to reduce calculation time.
  • Reduce Data Volume: Use filters and aggregations to limit the amount of data processed.
  • Optimize UI Design: Avoid excessive objects and use simple, effective visualizations.

Implementing these practices can significantly improve the responsiveness and efficiency of QlikView applications.

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