In today’s data-driven world, companies rely heavily on business intelligence (BI) tools to make informed decisions. Among the popular BI tools available, Qlik Sense stands out due to its user-friendly interface, powerful associative engine, and advanced analytics capabilities. Job seekers looking to enter the data and analytics field can benefit significantly from learning Qlik Sense, as organisations across various industries adopt it to drive insights and streamline operations.
This article delves into what Qlik Sense is, its key features, use cases, and the career prospects it offers. Furthermore, it explores the core concepts of Qlik Sense, such as data loading, modelling, and architecture, as well as provides sample interview questions for job seekers looking to prepare for Qlik Sense-related roles. Whether you are a beginner or an experienced professional, this comprehensive guide will help you gain a deeper understanding of Qlik Sense and how it can enhance your career in the BI field.
What is Qlik Sense?
Qlik Sense is a modern business intelligence tool developed by Qlik that helps users analyse data, create visualisations, and derive insights through interactive dashboards and reports. It enables users to access data from multiple sources, manipulate it using intuitive tools, and create meaningful visualisations that help in decision-making.
Key Features and Benefits
Qlik Sense offers numerous features and benefits that set it apart from other BI tools. Let’s explore some of its key features:
Associative Data Engine: Qlik Sense’s associative engine allows users to explore data freely, identifying associations across various datasets without predefined queries or joins. Unlike traditional query-based BI tools, Qlik Sense shows users how data fields are related, allowing for deeper exploration.
Self-Service Visualization: The platform is designed for self-service, meaning that both technical and non-technical users can create their own reports and dashboards without needing to rely on IT teams. The drag-and-drop interface makes it simple to build interactive visualisations in a few clicks.
Smart Search: Qlik Sense offers a smart search functionality, which allows users to search through data fields, providing quick access to insights without the need to navigate through the entire dataset. This feature makes it easier to find relationships and patterns in data.
Multi-Device Support: Qlik Sense is built to support multiple devices, including desktops, tablets, and mobile phones. Users can interact with dashboards and reports on the go, making it a versatile tool for real-time decision-making.
Data Integration: Qlik Sense can integrate data from various sources, including databases, web applications, cloud services, and spreadsheets. This flexibility allows users to consolidate their data in one place for more comprehensive analysis.
Governed Data Collaboration: Qlik Sense ensures that data shared among team members remains consistent and secure. It provides governed data collaboration, meaning that users across an organisation can access the same data and insights while ensuring data accuracy and security.
Advanced Analytics and Predictive Modeling: For more advanced users, Qlik Sense integrates with R and Python, allowing for predictive analytics and machine learning (ML) applications. This feature enables data scientists to apply complex statistical models to their datasets and generate predictions or recommendations.
Use Cases and Industries
Qlik Sense is widely used across industries due to its flexibility and scalability. Here are some examples of how different industries utilise Qlik Sense:
Retail: Retailers use Qlik Sense to analyse sales trends, customer behaviour, and inventory management. By visualising sales data, retailers can identify which products are performing well, optimise pricing strategies, and forecast demand.
Healthcare: In healthcare, Qlik Sense is used to analyse patient data, hospital performance, and treatment outcomes. Hospitals and clinics can use Qlik Sense to identify patterns in patient care, track treatment efficacy, and improve resource allocation.
Financial Services: Financial institutions use Qlik Sense for risk assessment, fraud detection, and regulatory compliance. By analysing transaction data and financial metrics, banks can detect anomalies, manage risk, and ensure compliance with industry regulations.
Manufacturing: In the manufacturing industry, Qlik Sense is used for supply chain optimization, production performance tracking, and quality control. Manufacturers can use it to analyse production data, reduce downtime, and improve overall efficiency.
Public Sector: Government agencies use Qlik Sense for policy analysis, resource allocation, and performance tracking. Public sector organisations rely on it to analyse large datasets, helping policymakers make informed decisions based on data.
Telecommunications: Telecom companies leverage Qlik Sense to analyse customer usage patterns, improve service delivery, and reduce churn. By analysing network performance and customer data, telecom providers can identify areas for improvement and optimise services.
Importance of Qlik Sense Proficiency for Job Seekers
As organisations increasingly rely on data to make informed decisions, there is a growing demand for professionals skilled in data analytics and BI tools like Qlik Sense. Proficiency in Qlik Sense can give job seekers a competitive advantage, making them more attractive to employers across various industries. Here are a few reasons why mastering Qlik Sense is essential for job seekers:
High Demand in the Market
The global BI market has seen significant growth in recent years. According to a report by MarketsandMarkets, the BI market was valued at $23.1 billion in 2018 and is projected to reach $33.3 billion by 2025, growing at a compound annual growth rate (CAGR) of 7.6%. As businesses prioritise data-driven decision-making, the demand for Qlik Sense professionals will continue to grow.
Career Opportunities and Growth Potential
Learning Qlik Sense opens the door to various career opportunities in roles such as:
- Data Analyst: Analyse data and provide insights to help organisations make informed decisions.
- BI Developer: Build, maintain, and manage BI applications and dashboards for business users.
- Data Engineer: Design and implement data pipelines and systems to facilitate data access and reporting.
- Data Scientist: Use Qlik Sense in combination with statistical modelling and machine learning to extract deeper insights from data.
Professionals skilled in Qlik Sense can also pursue advanced roles such as data architect, chief data officer (CDO), or head of BI, depending on their experience and expertise.
Salary Expectations
Salaries for Qlik Sense professionals vary depending on the job role, location, and level of expertise. In the United States, the average salary for a Qlik Sense developer ranges from $85,000 to $120,000 annually, depending on experience. Data analysts with Qlik Sense proficiency typically earn between $70,000 and $100,000, while BI managers can earn upwards of $120,000 per year. Globally, professionals with Qlik Sense expertise can expect competitive salaries across regions such as Europe, the Middle East, and Asia-Pacific, reflecting the high demand for BI talent.
Core Qlik Sense Concepts
To effectively use Qlik Sense, it’s crucial to understand its core concepts, including data loading, modelling, and cleansing. Mastery of these concepts ensures that you can manipulate and analyse data effectively.
Data Loading and Modeling
Data loading and modelling are fundamental to working with Qlik Sense, as they involve bringing data into the system and structuring it for analysis.
Different Data Loading Methods
Script Editor: Qlik Sense allows users to load data into the application using the script editor. The script editor provides users with control over how data is imported, allowing them to perform data transformations, filtering, and aggregation during the loading process.
Data Connections: Qlik Sense provides built-in data connectors that allow users to connect to various data sources such as databases (e.g., SQL, Oracle), spreadsheets (e.g., Excel), web services, and cloud platforms (e.g., AWS, Google Cloud). Data can be loaded seamlessly into Qlik Sense through these connections.
Data Load Wizard: For users who are less familiar with scripting, Qlik Sense offers a data load wizard, which provides a guided process to load data from various sources. This feature simplifies the process for non-technical users.
Data Modeling Techniques
Once the data is loaded, the next step is to model it for analysis. Qlik Sense provides several techniques to structure and organise data for more effective visualisation and analysis:
Associations: Qlik Sense uses an associative data model, where data is linked through associations rather than traditional joins. This means that users can see how different data fields are connected without writing complex join statements, making it easier to explore and understand relationships between data points.
Dimensions and Measures: In Qlik Sense, data fields are classified into dimensions and measures:
- Dimensions: These are descriptive data fields, such as product names, regions, or categories, used to group or categorise data.
- Measures: These are numeric data fields, such as sales totals or profit margins, that can be aggregated or calculated to provide insights.
- Synthetic Keys: When multiple tables are loaded into Qlik Sense, the system automatically identifies common fields between them and creates synthetic keys. Synthetic keys are used to establish relationships between data tables, but excessive synthetic keys can slow down performance, so managing them is important.
Data Cleansing and Preparation
Data cleansing is an essential step in preparing data for analysis. Qlik Sense provides various tools and functions for data transformation, allowing users to clean and prepare their data before it is used in visualisations.
- Handling Missing Data: Users can identify missing data using built-in functions, such as NullCount() or IsNull(), to find and handle incomplete data.
- Data Transformation: Qlik Sense allows users to apply transformations such as renaming fields, converting data types, or applying functions to clean data before analysis.
- Field Extraction: Users can extract parts of a field, such as extracting dates or text patterns, using Qlik Sense’s built-in functions like Substring() or Date().
Qlik Sense Architecture
Qlik Sense has a robust architecture that enables it to handle large datasets, provide fast data exploration, and support multiple users simultaneously. Understanding the architecture helps job seekers gain insights into how Qlik Sense performs its operations and how to optimise its performance.
Associative Engine and Its Benefits
At the heart of Qlik Sense is its associative engine, which is different from traditional query-based engines used in other BI tools. The associative engine enables users to explore data without needing predefined queries or views. It allows users to filter data interactively and see how different fields and data points are connected. This dynamic data exploration capability is one of the key reasons why Qlik Sense is so effective at uncovering hidden insights.
Benefits of the associative engine include:
- Flexibility: Users can freely navigate and explore data without needing to ask for specific reports or queries.
- Speed: Qlik Sense responds quickly to user inputs, as its engine caches frequently used data and precomputes associations.
- Reduced Complexity: The associative engine eliminates the need for complex SQL joins or data aggregations, making it easier for users to work with data.
Data Virtualization and Caching
Data virtualization allows Qlik Sense to work with data from various sources without physically moving the data to a central repository. This capability is crucial when working with large datasets from different databases or systems. Qlik Sense presents a unified view of the data, allowing users to analyse data from multiple sources in one place without needing to consolidate it manually.
Qlik Sense also uses caching to improve performance. When users interact with a dashboard, Qlik Sense stores frequently accessed data in memory, reducing the time required to reload the data for repeated queries. This makes the system faster and more responsive, especially when working with large datasets or complex calculations.
Multi-Tier Architecture Components
Qlik Sense’s multi-tier architecture consists of several components, each serving a different role in the system. These components work together to provide an efficient and scalable BI platform.
Data Tier: This is where raw data is stored. It can include databases, spreadsheets, and other data sources. Qlik Sense accesses this tier to load data into its application.
Application Tier: The application tier is where data models, calculations, and transformations are applied. In this layer, users define relationships between data tables, create measures and dimensions, and prepare the data for analysis.
Presentation Tier: The presentation tier is the front-end interface used by end-users to interact with visualisations, dashboards, and reports. This layer allows users to explore data, create visualisations, and share insights with others.
Qlik Sense Development
Qlik Sense development involves creating interactive dashboards, reports, and visualisations that provide valuable insights to business users. Job seekers aiming to become Qlik Sense developers or BI analysts need to understand how to build these applications effectively.
Chart Types and Their Usage
Qlik Sense provides a wide variety of chart types, each designed for specific types of data analysis. Some of the most common chart types and their use cases include:
Bar Charts: Bar charts are used to compare data across categories. They are ideal for visualising sales performance across different regions, products, or time periods.
Line Charts: Line charts are useful for showing trends over time. For example, businesses can use line charts to track revenue growth over months or years.
Pie Charts: Pie charts are used to show the proportion of different categories within a dataset. They are often used for visualising market share or customer segmentation.
Scatter Plots: Scatter plots show relationships between two variables. They are useful for identifying correlations, such as the relationship between advertising spend and sales revenue.
Heat Maps: Heat maps display data in a matrix format, with colours representing the magnitude of the values. Heat maps are useful for visualising data across two dimensions, such as sales by region and product category.
Treemaps: Treemaps are used to represent hierarchical data. They are helpful for visualising the breakdown of sales across product categories and subcategories.
KPIs: Key performance indicators (KPIs) provide a single metric that reflects the performance of a business goal, such as revenue, customer satisfaction, or profit margin.
Expressions and Calculations
Expressions in Qlik Sense are used to create custom calculations, measures, and visualisations. Job seekers aspiring to become Qlik Sense developers must be familiar with common expressions and functions to manipulate data effectively. Some key concepts include:
Aggregation Functions: Functions like Sum(), Avg(), Count(), and Min() are used to calculate aggregate values, such as the total sales or average order value.
Set Analysis: Set analysis allows users to define a specific subset of data within an expression. For example, a set analysis expression can be used to calculate sales for a specific year or region, making it useful for comparisons and filtering.
If Statements: The If() function is used to apply conditional logic to data. For example, you can use If() to create custom categories based on certain criteria, such as categorising sales as “high,” “medium,” or “low.”
String Functions: Functions like Substring() and Len() are used to manipulate text fields, such as extracting a part of a field or calculating the length of a string.
Date Functions: Date functions, such as Year(), Month(), and Day(), are used to extract specific components from date fields, allowing users to perform time-based analysis.
Master Items and Variables
In Qlik Sense, master items are reusable elements that can be used across multiple dashboards and applications. These include dimensions, measures, and visualisations that have been predefined by the user.
Master Dimensions: A master dimension is a reusable field that categorises data, such as “Region” or “Product Category.” Once defined, it can be used in multiple visualisations.
Master Measures: A master measure is a predefined calculation or metric, such as “Total Sales” or “Profit Margin.” Using master measures ensures consistency across visualisations.
Variables: Variables in Qlik Sense store dynamic values that can be used in expressions or calculations. For example, you can create a variable to store the current year or a specific filter value, making it easier to apply dynamic filtering across different visualisations.
Qlik Sense Analytics
Qlik Sense is not only a tool for building visualisations but also a comprehensive platform for performing advanced data analytics. By understanding how to create dashboards, perform predictive analytics, and tell stories with data, job seekers can position themselves as valuable assets in their future organisations.
Storytelling and Data Visualization
Data storytelling involves combining different visualisations into a coherent narrative that presents data-driven insights. Qlik Sense’s storytelling features enable users to craft data stories by assembling multiple visualisations into a sequence of slides or presentations. This feature is particularly useful for presenting findings to decision-makers or stakeholders.
A well-constructed data story allows users to guide their audience through the insights, helping them understand trends, relationships, and patterns in the data. With Qlik Sense, users can include interactive elements in their stories, allowing viewers to explore the data themselves and ask their own questions.
KPI and Dashboard Creation
Key performance indicators (KPIs) are critical to tracking the success of an organisation. Qlik Sense allows users to create KPIs that provide real-time insights into business performance. Dashboards are used to aggregate multiple KPIs and visualisations in one place, giving users a comprehensive view of their data.
To create effective dashboards, users must focus on key design principles, such as:
- Clarity: Ensure that each element on the dashboard is clear and easy to interpret. Avoid clutter and unnecessary information.
- Relevance: Focus on the most important KPIs and metrics that drive business decisions.
- Interactivity: Provide users with the ability to filter and interact with the data, allowing them to explore different dimensions and measures.
- Performance: Optimise dashboards for performance by reducing the number of complex calculations and limiting the amount of data loaded into the application.
Advanced Analytics
Qlik Sense offers advanced analytics capabilities that allow users to go beyond basic reporting and visualisation. These features enable businesses to apply statistical models, machine learning algorithms, and predictive analytics to their data.
Predictive Analytics
Predictive analytics involves using historical data to predict future outcomes. In Qlik Sense, users can integrate predictive models built using R or Python and apply them to their data. For example, a retail company might use predictive analytics to forecast sales trends based on past data, while a healthcare provider could use it to predict patient outcomes based on treatment history.
Machine Learning
Qlik Sense also supports the integration of machine learning models, allowing data scientists to apply algorithms to identify patterns in data and make predictions. For example, a machine learning model can be used to classify customer segments based on purchase behaviour or predict product demand based on historical data and external factors.
By combining machine learning with Qlik Sense’s visualisation capabilities, businesses can gain deeper insights into their data and make more informed decisions.
Qlik Sense Interview Questions and Answers
For job seekers preparing for roles involving Qlik Sense, it’s important to be familiar with both the technical and practical aspects of the tool. Below are common interview questions and their answers, categorised by topic.
Section 1: Basic Qlik Sense Concepts
1) What is the difference between a dimension and a measure?
A dimension is a descriptive data field used to group or categorise data (e.g., “Product Category”). A measure is a numeric data field that can be aggregated or calculated (e.g., “Total Sales”).
2) Explain the concept of associative data modelling in Qlik Sense.
Associative data modelling allows users to explore data relationships without predefined joins. This model enables users to freely navigate data and discover insights by interacting with different fields.
3) How do you handle missing or inconsistent data in Qlik Sense?
Missing data can be handled using functions like NullCount() or IsNull() to identify missing values. Inconsistent data can be cleaned using transformations during the data loading process, such as renaming fields or applying filters.
4) What is the purpose of a master item in Qlik Sense?
A master item is a reusable dimension, measure, or visualisation that ensures consistency across multiple applications and dashboards.
5) Describe the various chart types available in Qlik Sense and their use cases.
Common chart types include bar charts (for comparing categories), line charts (for visualising trends), pie charts (for showing proportions), scatter plots (for analysing relationships), and KPIs (for tracking key metrics).
Section 2: Qlik Sense Development and Analytics
1) How do you create a calculated field in Qlik Sense?
You can create a calculated field by writing an expression in the script editor or using the “Add Measure” option in the chart properties panel.
2) What are some common Qlik Sense expressions and functions?
Common expressions include Sum(), Avg(), Count(), Min(), and Max(). Functions like If(), Set Analysis, and string functions are also frequently used.
3) Explain the concept of set analysis and its applications.
Set analysis allows users to define a specific subset of data within an expression. It is commonly used to compare different time periods, such as calculating sales for the current year compared to the previous year.
4) How do you create a dashboard with interactive elements in Qlik Sense?
Interactive elements like filters, buttons, and dynamic charts can be added by using the drag-and-drop interface in Qlik Sense. Users can configure these elements to allow for real-time exploration of data.
5) What is the role of storytelling in data visualisation?
Storytelling involves creating a narrative using visualisations to guide the audience through the data. It helps convey insights more effectively and allows decision-makers to grasp the key findings quickly.
Section 3: Qlik Sense Architecture and Performance
1) Describe the components of a Qlik Sense architecture.
Qlik Sense architecture includes the data tier (where raw data is stored), the application tier (where data models and calculations are applied), and the presentation tier (where visualisations and dashboards are created).
2) How does data virtualization work in Qlik Sense?
Data virtualization allows Qlik Sense to present data from multiple sources as if it were stored in one place, without physically moving the data. This enables users to work with large datasets from different systems in a unified view.
3) What are some best practices for optimising Qlik Sense performance?
Best practices include optimising data models, reducing the number of synthetic keys, using efficient expressions, and caching frequently accessed data.
4) Explain the concept of data caching in Qlik Sense.
Data caching stores frequently accessed data in memory, reducing the need to reload it from the source for repeated queries, thus improving performance.
5) Discuss the challenges and solutions related to data security and governance in Qlik Sense.
Data security challenges include controlling access to sensitive data. Solutions in Qlik Sense include role-based access control (RBAC), encryption, and data lineage tracking to ensure data security and compliance.
Section 4: Advanced Qlik Sense Topics
1) What is Qlik Sense Mobile and its key features?
Qlik Sense Mobile is a mobile version of the platform that allows users to access dashboards and reports on smartphones and tablets. It supports offline access and provides interactive data exploration.
2) How can you integrate Qlik Sense with other BI tools or applications?
Qlik Sense can be integrated with other BI tools or applications using APIs, connectors, or custom scripts to create seamless data pipelines.
3) What are some common use cases for predictive analytics in Qlik Sense?
Predictive analytics is commonly used for forecasting sales, customer behaviour analysis, and risk assessment in industries such as retail, healthcare, and finance.
4) Discuss the role of machine learning in Qlik Sense.
Machine learning models can be integrated into Qlik Sense to provide deeper insights, such as classifying customer segments or predicting product demand. These models can be applied through integrations with R or Python.
5) What are the benefits of using Qlik Sense for data governance and compliance?
Qlik Sense offers features like role-based access control, data lineage tracking, and compliance reporting, which help businesses manage their data securely and ensure regulatory compliance.
Conclusion
Qlik Sense is a versatile and powerful business intelligence tool that provides significant value to organisations by enabling data-driven decision-making. For job seekers, gaining proficiency in Qlik Sense can open up a wide range of career opportunities, from data analysis to BI development.
By understanding key concepts like data loading, modelling, and visualisation, along with more advanced topics like predictive analytics and machine learning, professionals can position themselves for success in the growing field of business intelligence. Whether you’re just starting out or looking to advance your career, Qlik Sense offers a valuable skill set that is highly sought after in today’s data-driven market.
