Course Introduction
Organizations increasingly require flexible business intelligence solutions that enable employees to access, explore, interpret, and communicate information without relying entirely on specialized IT or data analytics teams. Qlik Sense provides a modern analytics environment that supports interactive data visualization, associative data exploration, self-service reporting, and informed decision-making across organizational functions. This course introduces participants to the principles, tools, and practical applications of Qlik Sense, with a focus on developing the technical and analytical capabilities needed to transform organizational data into meaningful business insights. It examines how self-service analytics can improve reporting efficiency, strengthen collaboration, and support a more data-driven organizational culture.
The programme explores the architecture, interface, and core capabilities of Qlik Sense, including its associative analytics engine, data model, visualizations, sheets, applications, and interactive exploration features. Participants will learn how Qlik Sense connects information from multiple sources and enables users to investigate relationships between data elements through its distinctive associative model. The course explains how this approach differs from conventional query-based reporting and how it helps users discover patterns, exceptions, and previously overlooked relationships. Emphasis is placed on understanding the Qlik Sense environment and applying its features to practical business intelligence requirements.
A significant component of the training focuses on data acquisition, preparation, transformation, and modeling. Participants will examine how to connect Qlik Sense to spreadsheets, relational databases, cloud platforms, and other enterprise information systems. They will learn how to use data load scripts, data manager capabilities, field transformations, associations, and data model viewer tools to prepare structured datasets for analysis. The programme also addresses common data quality challenges, including duplicate records, inconsistent formats, missing values, synthetic keys, circular references, and data granularity issues. These capabilities are essential for building reliable data models that support accurate analysis and consistent reporting.
The course further develops practical skills in creating interactive dashboards, visualizations, and self-service analytical applications. Participants will explore charts, tables, KPI objects, filters, selections, bookmarks, and other visualization features that enable users to examine information from different perspectives. They will learn how to design intuitive applications for sales performance, financial analysis, procurement, customer behavior, operational efficiency, and management reporting. Attention is also given to visualization principles, user experience, dashboard navigation, and storytelling techniques that make complex analytical information understandable and actionable for different organizational audiences.
In addition to core analytics capabilities, the programme considers collaboration, governance, security, and administration within Qlik Sense environments. Participants will examine application publishing, content sharing, user access, security rules, data refresh processes, and the management of shared analytical resources. Contemporary developments such as cloud analytics, automated data pipelines, embedded analytics, artificial intelligence-assisted insights, and augmented analytics are explored in relation to modern business intelligence strategies. The course also emphasizes responsible data use, access control, documentation, and quality assurance to ensure that self-service analytics remains secure, reliable, and aligned with organizational requirements.
By the end of the course, participants will have developed practical capabilities to use Qlik Sense for data integration, analysis, visualization, and self-service reporting. They will understand how to prepare analytical datasets, construct meaningful data models, develop interactive dashboards, and enable users to explore information independently. The knowledge gained will help organizations reduce dependence on manual reporting, improve access to timely management information, identify emerging business trends, and strengthen evidence-based decision-making. Participants will be better prepared to contribute to business intelligence initiatives and support the adoption of a sustainable self-service analytics environment.
Duration
5 days
Who Should Attend
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Business intelligence analysts and developers.
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Data analysts and data visualization specialists.
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Business analysts and management information officers.
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Qlik Sense developers and application designers.
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Database administrators and data management professionals.
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Financial analysts and management accountants.
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Sales and marketing performance analysts.
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Operations and supply chain analysts.
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IT managers and information systems administrators.
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Business intelligence project managers.
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Reporting and performance management officers.
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Data governance and data quality specialists.
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Strategic planning and corporate performance officers.
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Digital transformation and analytics consultants.
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Managers and executives responsible for data-driven decision-making.
Course Objectives
By the end of this course, participants will be able to:
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Explain the architecture, principles, and core capabilities of Qlik Sense and demonstrate how its associative analytics engine supports interactive business intelligence and self-service data exploration.
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Navigate the Qlik Sense environment and create analytical applications, sheets, visualizations, and reporting resources that address defined organizational information requirements.
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Connect Qlik Sense to spreadsheets, relational databases, cloud platforms, and enterprise information systems using appropriate data acquisition and integration methods.
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Apply data preparation, transformation, cleansing, and validation techniques to improve the accuracy, consistency, and usability of datasets used in business intelligence applications.
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Develop effective data models using associations, data load scripts, field transformations, and model inspection tools to support reliable analytical performance.
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Design interactive visualizations, KPI indicators, charts, tables, and dashboards that communicate operational, financial, commercial, and strategic performance information.
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Use selections, filters, bookmarks, associative exploration, and drill-down functionality to investigate relationships, identify trends, and discover business performance exceptions.
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Apply Qlik scripting and analytical expressions to develop customized calculations, business metrics, conditional logic, and advanced reporting functionality.
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Implement appropriate application sharing, user access controls, data refresh procedures, and governance practices to support secure and sustainable self-service analytics.
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Develop and present a practical Qlik Sense business intelligence application that demonstrates data integration, interactive analysis, visualization, and evidence-based reporting.
Comprehensive Course Outline
Module 1: Introduction to Qlik Sense and Business Intelligence
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Understanding business intelligence concepts, self-service analytics principles, and the role of modern analytics platforms in organizational decision-making.
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Exploring Qlik Sense architecture, including its associative analytics engine, applications, sheets, visualizations, and data management environment.
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Examining the differences between traditional reporting, guided analytics, self-service business intelligence, and augmented analytics.
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Navigating the Qlik Sense interface and understanding the functions of Qlik Sense Desktop, Qlik Cloud Analytics, and enterprise deployment environments.
Module 2: Data Connections, Acquisition and Preparation
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Connecting Qlik Sense to Excel files, CSV datasets, relational databases, cloud storage, and other supported enterprise information sources.
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Using data manager and data load capabilities to import, inspect, organize, and prepare datasets for analytical applications.
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Applying data cleansing, field renaming, filtering, formatting, and transformation techniques to improve source data quality.
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Identifying missing values, duplicate records, inconsistent field definitions, and data structure problems that may affect analytical reliability.
Module 3: Qlik Sense Data Modeling and Associative Analytics
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Understanding the associative data model and how Qlik Sense connects information across different tables and business entities.
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Creating table associations, managing keys, and establishing appropriate data relationships for integrated business analysis.
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Using the data model viewer to inspect table structures, identify synthetic keys, resolve circular references, and assess model integrity.
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Applying data modeling principles to develop efficient datasets for financial reporting, sales analysis, customer analytics, and operational monitoring.
Module 4: Qlik Data Load Scripting and Data Transformation
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Understanding Qlik load script structure, script editing, data loading procedures, and the use of script-based transformations.
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Applying script functions, conditional statements, resident loads, preceding loads, and field transformations to prepare complex datasets.
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Using joins, concatenation, mapping loads, and aggregation techniques to combine and reshape information from multiple sources.
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Developing reusable and documented data load scripts that improve data preparation consistency, maintainability, and reporting efficiency.
Module 5: Qlik Sense Visualizations and Interactive Dashboard Design
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Creating visualizations using bar charts, line charts, pie charts, tables, combo charts, scatter plots, and other suitable analytical objects.
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Developing KPI objects, measures, dimensions, labels, and expressions to communicate organizational performance and business indicators.
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Applying filters, selections, drill-down dimensions, and interactive navigation to enable users to explore information from different perspectives.
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Designing professional dashboards using appropriate layouts, visual hierarchy, color selection, accessibility principles, and analytical storytelling techniques.
Module 6: Self-Service Analytics and Associative Data Exploration
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Using the associative selection model to explore possible, selected, alternative, and excluded data values during business analysis.
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Applying selections, bookmarks, alternate states, and comparative analysis techniques to investigate different business scenarios.
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Enabling users to perform independent analysis through interactive applications without requiring extensive technical or scripting knowledge.
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Exploring self-service analytics use cases for customer segmentation, operational performance, financial trends, market analysis, and organizational reporting.
Module 7: Advanced Expressions, Calculations and Analytical Techniques
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Developing Qlik expressions using aggregation functions, conditional logic, set analysis, and dimensional calculations for advanced business reporting.
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Applying set analysis to compare reporting periods, isolate business segments, evaluate selected performance categories, and analyze filtered datasets.
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Using variables, dollar-sign expansions, and reusable expressions to create flexible calculations and dynamic analytical applications.
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Exploring advanced analytical capabilities, including comparative analysis, trend identification, forecasting concepts, and AI-assisted insight discovery.
Module 8: Business Intelligence Applications and Practical Use Cases
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Developing sales and marketing dashboards to monitor revenue performance, customer acquisition, product trends, and sales conversion indicators.
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Creating financial reporting applications for budget monitoring, expenditure analysis, profitability assessment, and financial performance evaluation.
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Building operational and supply chain dashboards to monitor inventory levels, procurement activities, production efficiency, and delivery performance.
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Applying Qlik Sense to human resource analytics, customer service reporting, project monitoring, and executive performance management.
Module 9: Collaboration, Security and Qlik Sense Administration
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Publishing and sharing Qlik Sense applications, managing shared content, and supporting collaboration across business departments.
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Understanding user access management, security rules, permissions, data access restrictions, and governance requirements in Qlik environments.
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Managing application updates, data reload schedules, monitoring processes, and refresh procedures to maintain timely reporting.
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Examining Qlik Cloud capabilities, enterprise administration considerations, embedded analytics, API integrations, and contemporary cloud-based BI developments.
Module 10: Practical Capstone Project and Implementation
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Identifying a business reporting requirement and preparing relevant datasets from multiple organizational sources for analysis.
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Building a structured Qlik Sense data model using appropriate associations, transformations, load scripts, and data quality controls.
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Developing an interactive self-service analytics application with dashboards, KPIs, calculated measures, filters, and associative exploration features.
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Presenting analytical findings and preparing recommendations for application deployment, user adoption, governance, and continuous improvement.
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808
Training Venue
The training will be held at our Upskill Training Centre. We also offer training for a group (at a discount of 10% to 50%) at requested location all over the world. The Onsite course fee covers the course tuition, training materials, two break refreshments, buffet lunch, airport transfers, Upskill gift package, and guided tour.
Visa application, travel expenses, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Upskill certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808
Terms of Payment:
Unless otherwise agreed between the two parties’ payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better.
