Veidlapa Nr. M-3 (8)
Study Course Description
Data-Based Decision-Making
Course Code
SZF_268
Branch of Science
Other engineering and technologies
ECTS
3.00
Target Audience
Biology; Business Management; Civil and Military Defense; Clinical Pharmacy; Communication Science; Dentistry; Digital Health; Health Management; Information and Communication Science; Juridical Science; Law; Life Science; Management Science; Marketing and Advertising; Medical Services; Medical Technologies; Medicine; Midwifery; Nursing Science; Pedagogy; Person and Property Defence; Pharmacy; Political Science; Psychology; Public Health; Rehabilitation; Social Anthropology; Social Welfare and Social Work; Sociology; Sports Science; Sports Trainer
LQF
Level 6
Study Type And Form
Full-Time
Study Course Implementer
Course Supervisor
Aldis Ērglis
Structure Unit Manager
Ieva Puzo
Structural Unit
Faculty of Social Sciences
Contacts
SZF, Kuldīgas iela 9c, szf@rsu.lv
About Study Course
Objective
The course aims to prepare students for the professional business environment by developing competencies across the full analytics cycle, ranging from problem definition to decision presentation. The curriculum utilises methodologies used by top-tier consulting firms, critical thinking frameworks, and principles of persuasive data communication.
Preliminary Knowledge
No technical prerequisites in data analysis are required. However, prior knowledge of business fundamentals—specifically understanding the link between goals, processes, and operational outcomes—is recommended.
Learning Outcomes
Knowledge
1.Identify and structure business problems
Individual work and tests
Independent work • Final test
2.Evaluate and select appropriate data analysis methods
Individual work and tests
Independent work • Analyze data with Power BI • Selecting data and applying data to an analytical task
3.Able to link business capabilities to digital solutions
Individual work and tests
Selecting data and applying data to an analytical task • Independent work
4.Persuasively present analysis results to management
Individual work and tests
Independent work • Final test
Skills
1.Able to develop a logical and structured design of the analytical task solution by transforming the business needs in a specific data exploration plan.
Individual work and tests
Final test • Selecting data and applying data to an analytical task
2.Able to select and apply appropriate modern quantitative analysis methods and techniques to solve specific business tasks and test hypotheses.
Individual work and tests
Analyze data with Power BI
3.Capable of meaningful data modelling and visualization by creating transparent schedules and dashboards (Dashboards) that clearly answer business questions.
Individual work and tests
Analyze data with Power BI • Selecting data and applying data to an analytical task
4.Able to identify and justify the added value generated by data analytics solutions, reports, and panels in the context of business efficiency or profit.
5.Able to use data analysis as a tool to explain, diagnose, and improve organization business models and processes.
Individual work and tests
Selecting data and applying data to an analytical task
6.Has acquired practical skills in the full data cycle, from data loading (from different sources) and preparation to modelling and visual representation of results.
Individual work and tests
Analyze data with Power BI • Final test
Competences
1.Will be able to independently structure ambiguous or complex business problems and design appropriate data analysis solutions using a hypothesis-driven approach (e.g., Issue Trees).
Individual work and tests
Application of strategic analysis tools • Final test • Selecting data and applying data to an analytical task
2.Will be able to justify the selection and application of appropriate strategic analysis tools (e.g., CATWOE, Fishbone) and decision-making methods (AHP) to ensure objective outcomes.
Individual work and tests
Selecting data and applying data to an analytical task • Final test • Application of strategic analysis tools
3.Will be able to select tools and analysis techniques appropriate to data analysis tasks.
Individual work and tests
Selecting data and applying data to an analytical task
4.Will be able to assess an organization's data literacy and analytics maturity level, capturing the current state (AS-IS) and developing recommendations for improvements in data culture and processes (TO-BE).
Individual work and tests
Application of strategic analysis tools • Final test
5.Will be able to transform complex data analysis findings into a persuasive business narrative, using structured argumentation principles (Minto Pyramid) for executive-level presentations.
Individual work and tests
Application of strategic analysis tools • Final test
Assessment
Individual work
|
Title
|
% from total grade
|
Grade
|
|---|---|---|
|
1.
Independent work |
20.00% from total grade
|
10 points
|
|
In independent work, students should create group work on topics acquired in the course by analysing project data, visualizing, drawing up recommendations. |
||
|
2.
Analyze data with Power BI |
20.00% from total grade
|
10 points
|
|
An end-to-end data analysis task, starting with defining an analytical task, loading, modelling, and visualising data. |
||
|
3.
Application of strategic analysis tools |
20.00% from total grade
|
10 points
|
|
Analysis task using strategic analysis tools, preparation of analysis results and effective presentation for management. |
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|
4.
Selecting data and applying data to an analytical task |
20.00% from total grade
|
10 points
|
|
Data selection and data acquisition methods according to the business task and technical solution. |
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Examination
|
Title
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% from total grade
|
Grade
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|---|---|---|
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1.
Final test |
20.00% from total grade
|
10 points
|
|
Develop a full-cycle analytical task using one of the methods and data analysis tools learned in the course. |
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Study Course Theme Plan
FULL-TIME
Part 1
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Topics
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Defining the Business Problem
Description
Identifying problems and opportunities, formulating a precise "Problem Statement," and developing hypotheses for further investigation. |
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Business Context and Analytical Frameworks
Description
Applying strategic analysis tools (e.g., CATWOE, PESTEL) to understand the organization's internal and external environment before starting data analysis. |
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Data literacy, data sources, their place in a modern organization
Description
Building a data culture within the company, classifying internal and external data sources, and understanding their role in the decision-making hierarchy. |
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Data Acquisition, Processing, and Evaluation
Description
Data quality criteria, fundamental cleaning principles, and preparing datasets to ensure reliable analysis results. |
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Class/Seminar
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On site
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2
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Topics
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Data Acquisition, Processing, and Evaluation
Description
Data quality criteria, fundamental cleaning principles, and preparing datasets to ensure reliable analysis results. |
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Location
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On site
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2
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Topics
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The Role of Causality in Data Analysis
Description
Distinguishing between correlation and causation. Root cause analysis methods (including Fishbone diagrams and 5 Whys) to identify the source of the problem. |
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Video Lecture
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On site
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2
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Data Analysis Methods and Tools
Description
Overview of descriptive and diagnostic analytics. How to select the most appropriate quantitative method for a specific business question. |
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On site
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2
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Topics
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Data Analysis Methods and Tools
Description
Overview of descriptive and diagnostic analytics. How to select the most appropriate quantitative method for a specific business question. |
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Class/Seminar
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Modality
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Location
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|---|---|---|
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On site
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2
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Visual Thinking and Data Representation Methods
Description
The psychology of visual perception and best practices for selecting the right charts and diagrams for clear data communication. |
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On site
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2
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Data Visualization and Modern Tools
Description
Practical information design and an introduction to modern BI (Business Intelligence) tools for creating interactive dashboards. |
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Class/Seminar
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Location
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On site
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Study room
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2
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Topics
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Data Visualization and Modern Tools
Description
Practical information design and an introduction to modern BI (Business Intelligence) tools for creating interactive dashboards. |
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On site
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2
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Business Capability-Based Approach and Link to Digital Solutions
Description
Modeling Business Capabilities and linking them to necessary technologies and digital transformation initiatives. |
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2
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Quantitative Definition of Digital Solutions
Description
Defining success metrics (KPIs) for new solutions and quantitatively forecasting expected outcomes. |
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On site
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2
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Data-Driven Solution Selection
Description
Evaluating and prioritizing alternatives using decision matrices and the AHP (Analytic Hierarchy Process). |
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On site
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Study room
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2
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Topics
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Preparing Structured Arguments for Management
Description
Synthesizing analysis results and presenting them using the Minto Pyramid principle to deliver persuasive recommendations to executive leadership. |
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Class/Seminar
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Modality
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Location
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Contact hours
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|---|---|---|
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On site
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Study room
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2
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Topics
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Preparing Structured Arguments for Management
Description
Synthesizing analysis results and presenting them using the Minto Pyramid principle to deliver persuasive recommendations to executive leadership. |
Total ECTS (Creditpoints):
3.00
Contact hours:
32 Academic Hours
Final Examination:
Exam
Bibliography
Required Reading
1.
G. Van Den Berg. 2014. Key Management Models. 3rd Edition. FT Publishing International.Suitable for English stream
2.
Barbara Minto. 2021. Pyramid Principle, The: Logic in Writing and Thinking. 3rd Edition. Pearson Education.Suitable for English stream
Additional Reading
1.
Thomas H. Davenport, Jeanne Harris. 2017. Competing on Analytics: Updated, with a New Introduction: The New Science of Winning. Harvard Business Review Press.Suitable for English stream