As organizations rely on business intelligence and interactive analytics to drive faster decisions, recruiters must identify QlikView professionals who can build powerful dashboards and data models. QlikView is widely used for self-service BI, data discovery, and associative analytics, enabling users to explore data beyond predefined queries.
This resource, "100+ QlikView Interview Questions and Answers," is tailored for recruiters to simplify the evaluation process. It covers a wide range of topics—from QlikView fundamentals to advanced dashboard development and data modeling, including Qlik scripting, associations, and performance optimization.
Whether you're hiring QlikView Developers, BI Analysts, Data Analysts, or Analytics Consultants, this guide enables you to assess a candidate’s:
For a streamlined assessment process, consider platforms like WeCP, which allow you to:
Save time, enhance your hiring process, and confidently hire QlikView professionals who can deliver fast, intuitive, and insight-driven BI solutions from day one.
QlikView is a Business Intelligence (BI) and data visualization tool developed by Qlik that allows users to transform raw data into meaningful insights through interactive dashboards and reports. It works on an in-memory associative data engine, which means all data is loaded into memory and users can explore it freely without predefined query paths.
Unlike traditional reporting tools that force users to follow fixed drill-down paths, QlikView enables free-form exploration. Users can click on any data point—such as a product, customer, region, or date—and instantly see how it relates to all other data. This makes QlikView especially powerful for data discovery, ad-hoc analysis, and decision support.
QlikView is widely used by business users, analysts, and developers to analyze large datasets quickly and intuitively without deep technical expertise.
QlikView offers a rich set of features that make it a powerful BI platform:
These features make QlikView suitable for both small analytical applications and large enterprise-level BI solutions.
QlikView is primarily used for data analysis, reporting, and decision-making. Organizations use QlikView to:
QlikView is especially valuable when users need fast insights and want to explore data without predefined questions. It is widely used in industries such as retail, banking, healthcare, manufacturing, and telecommunications.
Business Intelligence (BI) refers to the processes, tools, and technologies used to collect, analyze, and present business data to support better decision-making.
BI helps organizations:
A typical BI process includes:
QlikView is a BI tool that focuses strongly on interactive analysis and data discovery, making BI accessible to non-technical users.
The key difference lies in how users interact with data.
Traditional BI tools are typically:
QlikView, on the other hand:
In short, traditional BI answers known questions, while QlikView helps users discover unknown insights.
A QlikView document, saved with the extension .qvw, is the core file that contains:
The QVW file acts as a complete BI application. Once created, it can be opened in QlikView Desktop or published to QlikView Server for multiple users to access.
Each QVW is self-contained, meaning it includes both the data and the logic required to analyze that data.
The associative data model is the foundation of QlikView’s functionality. It automatically links data across tables based on common field names, without requiring predefined joins in queries.
Key characteristics:
This model enables users to see what is related and what is not, which is something traditional BI tools do not easily provide. It encourages deep exploration and insight discovery.
Dimensions are descriptive fields used to categorize or group data. They answer questions like who, what, where, and when.
Examples of dimensions:
Dimensions define how data is broken down in charts and tables. For example, when analyzing sales, “Region” might be a dimension that groups total sales by location.
Without dimensions, measures would have no meaningful structure.
Measures are numerical values that are calculated and analyzed. They typically involve aggregation functions.
Common examples:
Measures answer questions like how much, how many, or how often. They always depend on dimensions for context—for example, “Total Sales by Region.”
In QlikView, measures are defined using expressions and dynamically recalculate based on user selections.
A chart in QlikView is a visual representation of data that helps users understand patterns, trends, and comparisons.
Charts combine:
Common chart types include:
Charts in QlikView are fully interactive. When a user clicks on a chart element, it acts as a selection and instantly updates all other objects in the application, making analysis fast and intuitive.
QlikView provides a wide range of chart types that help users visualize data from different perspectives. Each chart serves a specific analytical purpose.
Common chart types include:
All charts in QlikView are interactive, meaning user selections in one chart automatically update all others, enabling fast and intuitive analysis.
A list box is one of the most fundamental selection objects in QlikView. It displays all possible values of a specific field, allowing users to filter data easily.
For example:
List boxes provide visual feedback using colors (green, white, grey), making it easy to understand data availability and relationships. They are essential for enabling user-driven analysis.
A selection in QlikView occurs when a user clicks or chooses one or more values from a field, list box, chart, or table.
Selections define the current context of analysis. For example:
QlikView is entirely driven by selections, allowing users to interactively explore data and instantly see how different data points relate to each other.
When a selection is made in QlikView:
This behavior allows users to explore data naturally, without needing to run new queries or reload data. It enables fast, intuitive insight discovery.
QlikView uses colors to show how data relates to current selections:
For example, if a user selects a specific product:
This color logic is a key strength of QlikView and helps users instantly understand data relationships.
A field in QlikView represents a column of data loaded from a data source. Fields form the foundation of the data model.
Examples of fields:
Fields are used to create:
Fields with the same name across tables are automatically associated, enabling QlikView’s associative data model.
The Script Editor is the area in QlikView where developers write and manage the data load script. It is used to extract, transform, and load data into the application.
Key purposes of the Script Editor:
The script runs only during reload, not during user interaction, and plays a critical role in application performance and accuracy.
A load script is a set of instructions written in QlikView’s scripting language that defines how data is loaded and prepared.
The load script typically performs:
Once executed, the processed data is loaded into memory and used for analysis. A well-written load script is essential for efficient, scalable QlikView applications.
A data source is the origin of data that QlikView loads for analysis. It can be internal or external.
Common data sources include:
QlikView can connect to multiple data sources in a single application, allowing organizations to combine and analyze data from different systems.
QlikView supports a wide variety of file formats, making it highly flexible.
Commonly supported formats include:
Among these, QVD files are the most efficient and are often used for performance optimization and data reuse.
Reload in QlikView is the process of executing the load script to fetch data from the defined data sources and load it into QlikView’s in-memory engine. During a reload, QlikView reads the script line by line, applies all transformations, calculations, joins, and mappings, and then builds the data model.
Reload is required whenever:
There are two types of reloads:
Reloading ensures that users always analyze fresh and accurate data.
A straight table is a simple tabular chart in QlikView that displays data in rows and columns, similar to an Excel table.
Characteristics of a straight table:
Example:
Straight tables are best used when users need precise values and detailed comparisons rather than high-level visual summaries.
A pivot table is an advanced tabular chart that allows users to analyze hierarchical data across multiple dimensions.
Key features:
Example:
Pivot tables are ideal for complex analytical scenarios where users need to explore data at different levels of detail.
An expression in QlikView is a formula used to calculate values dynamically within charts, tables, and KPIs. Expressions typically include aggregation functions, conditions, and field references.
Examples:
SUM(Sales)COUNT(DISTINCT CustomerID)AVG(Profit)Expressions recalculate instantly based on user selections, making them central to QlikView’s interactive analytics capability.
Aggregation functions perform calculations on multiple rows of data and return a single result. They are essential for summarizing data.
Common aggregation functions include:
SUM() – Adds valuesCOUNT() – Counts recordsAVG() – Calculates averageMIN() – Returns minimum valueMAX() – Returns maximum valueThese functions are widely used in expressions to produce meaningful metrics such as totals, averages, and counts.
The SUM() function calculates the total of numeric values for a given field.
Example:
SUM(Sales)
If a user selects a specific region or product, the SUM function automatically recalculates to show totals only for the selected data. This dynamic behavior makes SUM one of the most frequently used functions in QlikView.
The COUNT() function counts the number of non-null records in a field.
Examples:
COUNT(OrderID) – Counts ordersCOUNT(DISTINCT CustomerID) – Counts unique customersCOUNT is often used to measure volume, frequency, or activity levels and is essential for KPIs like number of transactions or customers.
The AVG() function calculates the average value of a numeric field.
Example:
AVG(Sales)
It divides the sum of values by the number of records. Like other aggregation functions, AVG recalculates dynamically based on selections, enabling real-time comparison and performance analysis.
A calendar in QlikView is a date-based structure used to analyze data across time.
It typically includes:
Calendars allow users to filter and analyze data by time periods, such as monthly sales trends or yearly performance comparisons.
A master calendar is a centralized date dimension created in the load script to ensure consistent time-based analysis across the application.
Benefits of a master calendar:
A master calendar is considered a best practice in QlikView development, especially for enterprise-level applications.
Section Access is a security feature in QlikView used to control who can see which data inside a QlikView application. It works by reducing data based on user credentials when the document is opened.
In simple terms, Section Access allows:
For example, a regional manager may only see data related to their own region, while an admin can see all data. Section Access is defined in the load script and is applied automatically at document open time.
QlikView Server is a centralized platform that allows multiple users to access QlikView documents through a web browser or client interface.
Key responsibilities of QlikView Server include:
QlikView Server enables enterprise-wide BI deployment, making dashboards available securely and consistently across an organization.
QlikView Desktop is a development and analysis tool used to create, edit, and test QlikView applications (.qvw files).
It allows developers to:
QlikView Desktop can also be used by individual users for offline analysis. However, it is not meant for large-scale multi-user access like QlikView Server.
Excel is primarily a spreadsheet tool, while QlikView is a Business Intelligence platform.
Key differences:
QlikView is more suitable for enterprise analytics, while Excel is best for small-scale calculations and personal analysis.
A sheet in QlikView is a workspace or canvas where charts, tables, and objects are placed.
Key points:
Sheets help structure dashboards logically, making applications easier to understand and use.
An object in QlikView refers to any visual or interactive component placed on a sheet.
Common objects include:
Objects enable users to interact with data, apply filters, and view results. Together, they form the user interface of a QlikView application.
A text object is used to display static or dynamic text within a QlikView document.
Uses of text objects include:
Text objects enhance usability and clarity by guiding users and highlighting key information.
A button object is an interactive element that allows users to trigger predefined actions with a single click.
Common button actions include:
Buttons improve user experience by simplifying navigation and reducing manual steps.
A document reload failure occurs when QlikView is unable to complete the data load process successfully.
Common causes include:
When a reload fails, data is not updated, which can lead to outdated or incorrect analysis. Reload logs help identify and fix such issues.
Some common beginner mistakes in QlikView include:
Avoiding these mistakes helps build efficient, scalable, and maintainable QlikView applications.
The QlikView associative engine is the core technology that differentiates QlikView from traditional BI tools. It stores all loaded data in memory and automatically creates associations between tables based on common field names. These associations allow users to explore data freely without predefined drill paths.
Key characteristics of the associative engine:
The engine uses a symbol-based, compressed in-memory structure, which enables fast calculations even on large datasets. When a user makes a selection, the engine recalculates possible values across all related fields in real time.
This approach supports discovery-based analytics, allowing users to answer both known and unknown business questions interactively.
A synthetic key is an automatically generated table created by QlikView when it detects multiple common fields between two or more tables.
QlikView creates synthetic keys to manage ambiguous associations. These keys are named like:
$Syn 1
$Syn 2
Synthetic keys indicate a data model issue, not a feature. While QlikView can still function with synthetic keys, they often lead to:
In professional QlikView development, synthetic keys are generally avoided.
Synthetic keys occur when:
Example:
If Table A and Table B both contain:
QlikView creates a synthetic key combining these fields to resolve ambiguity.
Common causes:
Synthetic keys can be removed using several best-practice techniques:
Removing synthetic keys improves performance, clarity, and data accuracy.
A circular reference occurs when three or more tables are linked in a loop, creating multiple paths between the same tables.
Example:
Circular references cause ambiguity in data associations and can lead to:
QlikView detects circular references and flags them as data model problems.
Circular references can be resolved using the following techniques:
Proper resolution ensures predictable analytics and accurate results.
The data model viewer is a visual representation of the data structure inside a QlikView application. It shows:
Benefits of the data model viewer:
It is one of the most important tools for intermediate and advanced QlikView developers.
A star schema is a data modeling design where a central fact table is connected to multiple dimension tables, forming a star-like structure.
Characteristics:
Example:
Star schema is considered best practice in QlikView because it:
A snowflake schema is a variation of the star schema where dimension tables are normalized into multiple related tables.
Characteristics:
Example:
While snowflake schema can reduce storage, it often introduces complexity and performance overhead in QlikView.
AspectStar SchemaSnowflake SchemaStructureSimple and flatComplex and normalizedPerformanceFasterSlowerMaintenanceEasyComplexSynthetic Key RiskLowHigherQlikView SuitabilityHighly recommendedLess preferred
Conclusion:
Star schema is generally preferred in QlikView due to its simplicity, performance efficiency, and alignment with the associative engine.
A resident load is a QlikView load technique where data is loaded from an already loaded in-memory table instead of directly from an external data source.
Key points:
Example use cases:
Resident loads are essential for building efficient, layered QlikView scripts.
A preceding load is a load structure where a LOAD statement is placed before another LOAD or SQL SELECT, allowing transformations before data is fully loaded.
Key benefits:
Example usage:
Preceding loads are often used to clean and transform raw data efficiently.
Incremental load is a technique where only new or changed data is loaded instead of reloading the entire dataset every time.
Benefits:
Incremental loads are especially useful when working with large transactional systems where full reloads are expensive.
Incremental load is typically implemented using:
Basic approach:
This approach ensures data freshness with optimal performance.
ApplyMap() is a QlikView function used to map values from one table to another using a mapping table.
Key characteristics:
Example use cases:
ApplyMap() is a best practice for efficient data enrichment.
AspectApplyMap()JoinPurposeValue lookupTable mergingPerformanceFasterSlowerData Size ImpactNo duplicationCan increase sizeUse CaseSingle-field mappingMultiple fieldsBest PracticePreferred for lookupsUse cautiously
ApplyMap() is preferred when only one field needs to be mapped, while joins are used when multiple fields are required.
A mapping table is a special two-column table used with ApplyMap() to perform value lookups.
Structure:
Characteristics:
Mapping tables help maintain clean, optimized data models.
Set analysis is an advanced QlikView expression feature that allows developers to define a fixed subset of data for calculations.
Key points:
Common use cases:
Set analysis enables powerful business logic inside expressions.
AspectSet AnalysisIF ConditionEvaluation TimeBefore aggregationRow-levelPerformanceFasterSlowerUse CaseStatic conditionsDynamic row logicSelection DependencyMostly independentFully dependent
Set analysis is preferred for performance and clarity, while IF is used when row-level conditions are required.
A calculated dimension is a dynamic dimension defined using an expression rather than a single field.
Examples:
Calculated dimensions:
They are useful for advanced analytical scenarios but should be used carefully due to performance considerations.
A calculated measure is a dynamic numeric expression used in QlikView to calculate values such as totals, averages, ratios, or KPIs based on the current selection state.
Calculated measures:
SUM(), COUNT(), AVG()Examples:
SUM(Sales)SUM(Profit) / SUM(Sales)Calculated measures enable business logic implementation directly in dashboards and are central to meaningful analytics.
An alternate state in QlikView allows users to create independent selection contexts within the same application.
Key points:
Example:
Alternate states enhance comparative and advanced analytical capabilities.
Alternate states are used when:
Example use cases:
They are especially useful in executive and analytical dashboards.
A canonical date is QlikView’s internal numeric representation of dates. It stores dates as numbers while displaying them in a human-readable format.
Key concept:
DD-MM-YYYY)Canonical dates ensure:
Understanding canonical dates is essential for correct date handling.
Date formats are handled using:
Date() – Formatting displayDate#() – Interpreting input datesTimestamp() / Timestamp#()DateFormatBest practices:
Correct date handling prevents data inconsistencies and calculation errors.
The dual() function assigns both a numeric value and a textual value to a field.
Syntax:
dual(text, number)
Use cases:
Example:
dual('High', 3)
Dual enables flexible display with correct sorting and calculations.
AutoCalendar is QlikView’s automatic date field generation feature that creates time-based fields from date values.
It automatically generates:
While useful for quick analysis, AutoCalendar:
Experienced developers prefer custom master calendars for better control.
Dollar-sign expansion ($()) is used to substitute variable values into expressions or scripts at evaluation time.
Example:
SUM(Sales) * $(vTaxRate)
Key characteristics:
Dollar-sign expansion enables dynamic, reusable, and parameter-driven logic.
A variable in QlikView is a named container that stores a value or expression for reuse.
Types of variables:
Use cases:
Variables help create clean, scalable, and maintainable QlikView applications.
AspectLETSETEvaluationEvaluates expressionAssigns literal textCalculationYesNoUse CaseNumeric resultsExpressions or stringsExampleLET vSum = 5+5SET vExp = SUM(Sales)
Conclusion:
Understanding this difference is crucial for correct variable behavior.
Script error handling in QlikView refers to the techniques used to detect, manage, and respond to errors that occur during script execution (reload).
Common script errors include:
QlikView provides mechanisms such as:
ErrorMode (controls whether reload stops on error)Proper error handling ensures stable reloads, reliable data, and easier troubleshooting, especially in production environments.
A log file is an automatically generated text file created during a QlikView reload that records detailed information about the script execution.
Log files include:
Log files are essential for:
They are a critical diagnostic tool for intermediate and advanced developers.
Load script performance optimization focuses on reducing reload time and memory usage.
Best practices include:
Optimized scripts result in faster reloads, lower server load, and better scalability.
A join in QlikView is a method of combining data from two tables based on common fields.
Joins are executed during script reload and physically merge tables in memory.
Use cases:
While joins are powerful, excessive use can:
Joins should be applied carefully and intentionally.
QlikView supports the following join types:
Each join type determines how unmatched records are handled. Selecting the correct join is essential for data accuracy and completeness.
AspectJoinConcatenatePurposeMerge columnsAppend rowsStructureHorizontal mergeVertical mergeData VolumeCan increase widthIncreases row countUse CaseEnrich recordsCombine similar datasetsRiskSynthetic keys, duplicationSchema mismatch
Use Join when adding attributes and Concatenate when stacking similar data structures.
NoConcatenate is a QlikView keyword used to prevent automatic concatenation of tables with identical structures.
By default, QlikView automatically concatenates tables with the same field structure. Using NoConcatenate forces QlikView to treat the table as a separate entity.
Use cases:
NoConcatenate helps maintain script clarity and data model integrity.
Section Application is the standard data section of the QlikView load script where actual business data is loaded.
Key points:
Section Application keywordSection AccessWithout Section Application, the document would contain security rules but no analytical data. It is the foundation of every QlikView application.
QVD (QlikView Data) files are native, highly optimized binary files used to store data extracted and processed by QlikView.
Characteristics:
QVD files act as building blocks for scalable QlikView architectures.
Benefits of QVD files include:
QVD usage is considered a best practice for enterprise-level QlikView development and is essential for handling large, complex data environments.
QlikView’s internal architecture is built around a high-performance, in-memory associative engine. The core components include:
Data is loaded into memory in a symbol table and bit-storing structure, enabling extremely fast calculations and selections. The architecture is designed for read-heavy analytical workloads, not transactional processing.
QlikView loads all data into RAM using a columnar, compressed structure. Each unique value is stored once in a symbol table, while records reference these symbols using pointers.
Key benefits:
Because calculations occur in memory, QlikView avoids repeated database queries, making it ideal for interactive analytics at scale.
Best practices include:
A clean data model ensures accurate results, better performance, and easier maintenance.
Scalable QlikView applications are designed by:
Scalability ensures the application can handle more data, more users, and more complexity over time.
Layered QVD architecture is a structured approach to data handling using QVD files across multiple layers.
Typical layers:
This approach improves:
It is a gold standard in enterprise QlikView implementations.
This separation ensures clean architecture and faster development cycles.
Managing large data volumes involves:
These techniques allow QlikView to handle millions to billions of records efficiently.
Application performance is optimized by:
Performance tuning ensures fast user interaction and server stability.
Common causes of slow reloads include:
Identifying and fixing reload bottlenecks is critical for production reliability.
Document size can be reduced by:
Smaller documents load faster and use less server memory.
An optimized QVD load occurs when QlikView reads a QVD without transformations, allowing it to load data directly into memory using its internal structure.
Conditions for optimized load:
Optimized loads are significantly faster than non-optimized loads.
QlikView compresses data using:
This reduces memory footprint dramatically, often achieving 10x or more compression, while still allowing instant access to data.
Complex set analysis involves advanced expressions that include:
Used for:
It allows powerful, fixed-logic calculations independent of user selections.
Advanced set modifiers include:
$()Example use cases:
Advanced set modifiers enable enterprise-grade analytics logic.
They are used inside set analysis to:
These functions unlock deep associative analysis capabilities.
Advanced dollar-sign expansion is used when:
Example use cases:
It enables highly flexible and dynamic expressions.
A cyclic dimension allows users to cycle through multiple dimensions within a single chart.
Example cycle:
Benefits:
It is useful when users want multiple views of the same measure.
A drill-down dimension allows users to progress hierarchically through dimensions.
Example:
Drill-down is structured and follows a fixed hierarchy, making it ideal for time-based analysis.
AspectCyclicDrill-DownNavigationSwitch manuallySequentialHierarchyIndependentFixedFlexibilityHighModerateUse CaseExplorationStructured analysis
Both enhance usability but serve different analytical needs.
Expression optimization is the practice of writing efficient, readable, and high-performance expressions.
Techniques include:
Optimized expressions improve chart performance, reload speed, and maintainability.
Debugging complex expressions in QlikView requires a systematic and layered approach.
Best practices include:
Advanced developers often isolate expression logic into variables, which improves readability, reuse, and debuggability.
Section access reduction is the process by which QlikView filters data at document open time based on user credentials defined in the Section Access table.
Key points:
It ensures data-level security and prevents unauthorized access to sensitive information.
Row-level security is implemented using Section Access in the load script.
Steps:
Best practices:
This approach ensures secure multi-user applications.
Common pitfalls include:
Improper Section Access can lead to data leakage or complete data loss, making careful design essential.
Document chaining allows users to navigate from one QlikView document to another, passing selections between documents.
Use cases:
Document chaining improves scalability and maintainability but must be implemented carefully to preserve context and security.
Loops and Peek are scripting techniques used for iterative processing.
Use cases:
These techniques enable advanced automation and dynamic scripting.
While Load is a scripting construct used to generate rows dynamically based on conditions.
Example use cases:
While loads execute during reload and are useful for controlled data generation.
Managing multi-fact tables requires careful modeling:
Best practices:
This ensures correct aggregations and performance across multiple business processes.
Slowly Changing Dimensions (SCDs) are handled by:
In QlikView:
Proper SCD handling ensures accurate historical analysis.
Publisher is required for:
Together, they enable enterprise-grade BI operations.
Reload scheduling automates data refresh using QlikView Publisher.
Benefits:
Scheduling is critical for production reliability and SLA compliance.
Monitoring includes:
Tools include:
Monitoring ensures system stability and proactive issue resolution.
Concurrent users are handled by:
Well-designed applications scale smoothly to hundreds or thousands of users.
Governance best practices include:
Strong governance ensures trust, compliance, and maintainability.
Version control strategies include:
Proper version control prevents regressions and deployment risks.
Migration involves:
Migrations may be between environments, servers, or toward modern platforms like Qlik Sense.
Security audits involve:
Regular audits prevent security breaches and compliance failures.
Common issues include:
Experienced developers rely on monitoring, logs, and alerting to resolve issues quickly.
Future-proofing involves:
This ensures longevity despite data growth and platform evolution.
An expert QlikView developer:
Expertise lies not just in syntax, but in architectural thinking and business alignment.
