University of Oulu Business Analytics SEIS Master's Thesis Guide: II00BD01, 30 ECTS, II00BC92 Maturity Test, Optional Seminar and Laturi

Quick answer: what is the University of Oulu Business Analytics SEIS thesis route?

The current Business Analytics - Software Engineering and Information Systems path at the University of Oulu leads to a Master of Science degree. The programme is a two-year, 120 ECTS international Master’s route, and the current 2026-2027 Peppi programme object is 52632 / IMP2026BASEIS. The exact thesis is II00BD01 Master’s Thesis, Business Analytics (Software Engineering and Information Systems), 30 ECTS, Peppi object 54307, classified as Advanced Studies, taught in English and graded 1-5/FAIL. The same programme requires II00BC92 Maturity test for Master’s Degree, Software Engineering and Information Systems, 0 ECTS, assessed pass/fail.

A separate 813627S Master’s Thesis Seminar, 2 ECTS exists in the current programme, but it is listed under other optional SEIS studies, not inside the mandatory 30 ECTS thesis and maturity module. This is an important distinction. The seminar can support thesis progress, but it should not be presented as a compulsory extra two-credit thesis requirement for every student. The current SEIS route also uses a supervisor and second examiner in Laturi, but its evaluation criteria are programme-specific, so the CSE numerical score mapping must not be copied into this guide.

1. Confirm that your degree path is SEIS

Business Analytics has three degree-specific paths. The SEIS route awards Master of Science and prepares students for an Information Analyst profile. The Business path awards MSc in Economics and Business Administration, while the Computer Science and Engineering path awards MSc Technology. Shared analytics courses do not make the thesis routes interchangeable. Before following thesis instructions, confirm that your current Peppi programme is 52632 Business Analytics, Software Engineering and Information Systems (MSc.), International Programme 2026-2027.

2. The exact current thesis is II00BD01 and it is 30 ECTS

Current programme 52632 places II00BD01 Master’s Thesis, Business Analytics (Software Engineering and Information Systems) in the mandatory Master’s Thesis and Maturity test module. The thesis is 30 ECTS. The current course object is 54307, its level is Advanced Studies, the primary teaching language is English and the assessment scale is 1-5/FAIL. Timo Koivumäki is listed as the current person in charge on the course object.

3. The current thesis realization is II00BD01-3001

The current official realization record identifies II00BD01-3001 for the 2026-2027 academic cycle. The realization begins at the start of August 2026 and continues through the end of July 2027. Administrative dates can change in later curricula, so use this implementation only for the current evidence period. If your own Peppi view differs, the live study plan and thesis administration should take priority.

4. The thesis must belong to software engineering or information systems

Current SEIS guidance states that the thesis must address a problem in software engineering or information systems. A topic may come from the student’s own interests, a supervisor or a company, but the supervisor helps align the work to the scientific field. This means a generic analytics project is not automatically an SEIS thesis. The research problem should connect the analytics work to an SEIS perspective such as system development, software quality, information systems use, organisational processes, UX, digital transformation or another relevant area.

5. Start thinking about the thesis before the second year is already advanced

The current SEIS thesis page describes late spring of the first Master’s year or early autumn of the second year as the typical starting period. The programme also organises thesis information events. The student remains responsible for starting the process and finding a supervisor. Early planning is useful because company access, personal-data permissions, research ethics or software-system access can take longer than the writing itself.

6. Start the formal process in Laturi

The current Business Analytics Information Processing Science/SEIS route uses Laturi for thesis launch, supervision, monitoring, evaluation and publication. Set up the process with the correct programme and supervisor information before the thesis is close to completion. Laturi should be treated as part of the formal academic workflow, not only as the final upload site.

7. Prepare the maximum-one-A4 research plan carefully

Current Business Analytics thesis guidance uses a research plan of maximum one A4 page. It should state the purpose, methods, materials, devices or software and expected results. Because the space is limited, write the plan around the research logic rather than general background. State the problem, research question, evidence or artefact, research approach, evaluation method and expected contribution. Supervisors approve the plan in Laturi.

8. Use the SEIS thesis template and instructions

The University page provides a Business Analytics Information Processing Science thesis template and programme-specific instructions. Use these rather than the BA-CSE thesis template. Formatting is not only cosmetic. The template usually reflects the structure and metadata expected by the programme and Laturi process. If a company gives its own report template, the academic thesis still needs to satisfy the University format.

9. The current SEIS route uses a supervisor and second examiner

The current Business Analytics Information Processing Science route states that the supervisor and second examiner evaluate the thesis in Laturi. They first discuss and agree on the evaluation. The supervisor enters the evaluation, after which the second examiner joins it in the system. This evaluation structure is different from the Oulu Business School Business path and should be kept separate.

10. Do not import the CSE score mapping into SEIS

The exact thesis course establishes a 1-5/FAIL scale, and the current University page links separate evaluation criteria for Business Analytics Information Processing Science. The CSE path publishes its own 10-42 score-to-grade mapping, but that mapping should not be applied automatically to SEIS. Use the current SEIS criteria for quality planning and final assessment.

11. External company work can include customer evaluation

When a thesis is done for an external customer, the current Business Analytics process provides a customer evaluation form. Company feedback can inform the academic process, but it does not replace University assessment. Keep company objectives and academic criteria aligned from the start. A technically useful solution may still need stronger research design, theoretical grounding or evaluation to satisfy Master’s-level standards.

12. The optional 813627S seminar exists, but it is not mandatory thesis credit

Programme 52632 lists 813627S Master’s Thesis Seminar, 2 ECTS under other optional SEIS studies. It is not inside the mandatory 30 ECTS thesis and maturity module. Therefore, the seminar should be described as an optional supporting course, not as an extra two-credit requirement that every Business Analytics SEIS student must complete. Check your PSP if you plan to include it.

13. The optional seminar can still be very useful

The current 813627S course supports thesis initiation and progress. It follows three broad phases: forming the topic, questions, literature review and method; collecting and analysing data; and discussing results, writing conclusions and presenting the final thesis. Students present their own work, review peers, write peer reviews and rebuttals, and become familiar with thesis evaluation criteria. This can be especially useful if you want structured feedback beyond individual supervision.

14. Research Methods provides the core methodological framework

813621S Research Methods is directly relevant to SEIS thesis planning. It covers scientific principles, research ethics, methodological quality and research approaches used in information systems and software engineering. The course explicitly covers qualitative research, quantitative research and design science research. It also expects students to select and apply an appropriate method for the Master’s thesis.

15. Advanced Research Methods goes deeper into research design

812649S Advanced Research Methods develops the philosophical assumptions and guiding principles behind qualitative, quantitative and design science research. It also covers research design, data collection, analysis, advanced analysis methods, reporting and evaluation of methodological quality. The course is recommended before or during thesis work. Use it to improve the logic connecting your research question, evidence and method.

16. Choose qualitative, quantitative or design science based on the question

There is no single required SEIS thesis method. A qualitative study may be suitable for understanding practices, experiences or organisational processes. A quantitative study may test relationships, compare groups or model data. Design science may be suitable when creating and evaluating an artefact such as a system, method, model or design. The method should follow the research problem rather than being chosen first and justified afterward.

17. Design science needs both construction and evaluation

A design science thesis should explain what artefact is built, which problem it addresses and why the design choices are justified. It should then evaluate the artefact using evidence appropriate to the claim. A working prototype alone does not prove research contribution. Define whether the evaluation concerns usefulness, usability, performance, correctness, organisational fit or another quality dimension and explain how that dimension is measured.

18. Qualitative studies need an explicit analysis procedure

If your thesis uses interviews, observations, documents or case-study material, explain how participants or cases were selected, how data were collected and how analysis was performed. Do not stop at saying that interviews were “analysed thematically” without describing the coding or interpretation process. The programme’s methodology courses place strong emphasis on methodological quality, so the analysis should be transparent enough for the reader to understand how conclusions were produced.

19. Quantitative studies need validity and generalisability planning

Current Statistical Methods for Business Analytics explicitly discusses validity, reliability and generalisability. If the thesis uses survey data, logs, transactions or experiments, explain whether the variables measure the intended concepts, whether repeated observations are independent, how missing data are handled and what population the results can support. Statistical output is only useful when the underlying design justifies the claim.

20. Data analytics should document the full evidence chain

Current Data Analytics and Business Intelligence studies cover data gathering, preparation, modelling, analysis, visualisation and communication. A thesis should make this chain visible. Record data sources, transformations, exclusions, model settings and output logic. A polished dashboard or model is not enough if the reader cannot see how the result was produced.

21. Data preprocessing belongs in the Methods chapter

Towards Data Mining covers combining sources, normalisation, transformations, missing or incorrect values and validation/generalisation. These are methodological decisions. If cleaning removes cases or changes distributions, report it. If features are derived from raw data, record the rule. If preprocessing parameters are estimated from the data, make sure final test information does not leak into development decisions.

22. Predictive work needs a separate final evaluation

If the thesis develops a prediction model, separate model development from final performance estimation. Feature selection, threshold choice and hyperparameter tuning should be based on training or validation data. A final test set intended to estimate generalisation should remain outside those decisions. Otherwise, performance can look better than it would on truly unseen data.

23. Grouped or temporal data need the right validation split

Random row splitting can be misleading when multiple records come from the same customer, user, company, project or time period. If the intended deployment is to new users or future time periods, the validation design should reflect that. Grouping or chronological splitting may be more appropriate. Explain why the chosen split represents the real decision context.

24. Information Systems Strategy can shape organisational thesis questions

817618S Information Systems Strategy and Leadership focuses on aligning information systems with organisational goals, analysing changing environments and making well-grounded recommendations. This is useful for theses on analytics adoption, digital transformation, information systems strategy or organisational capability. Recommendations should be linked to evidence and context, not only to general best practices.

25. Creating Domain Value with Data connects analytics to organisational value

817615S Creating Domain Value with Data examines how organisations use analytics for competitive advantage, decision-making, capability development and analytics maturity. If the thesis builds an analytics solution, explain how value is expected to arise. A technical output should be linked to a specific decision, process, capability or stakeholder need. Otherwise, a claim that the system “creates business value” may be too broad.

26. UX and usability theses need participant and task design

812671S User Experience and Usability Evaluation covers evaluation processes, test scenarios, tasks, participant selection, methods, metrics, field/lab execution, analysis and reporting. A UX thesis should describe who participated, why they were relevant, what tasks they performed and how the outcomes were measured. Small usability samples can still be useful, but conclusions should match the tested users and context.

27. Human and societal effects may be part of an SEIS thesis

817619S Societal and Individual Impacts of Information Systems addresses how ICT affects communication, behaviour and society. If the thesis studies persuasive systems, digital interventions, social platforms or organisational technologies, consider whether the system changes behaviour or relationships. Technical functionality alone may not explain the full outcome.

28. Software engineering studies need empirical evidence

815663S Software Engineering Research focuses on empirical research design, critical analysis of scientific papers and adapting research methods to software engineering. A software thesis should make empirical evidence visible. If the claim concerns productivity, quality, developer behaviour or process improvement, define the units, data source and comparison used to support the claim.

29. Software quality and security require measurable criteria

811602S Advanced Software Quality and Security includes test automation, code review, static analysis, test-driven development and security testing. If the thesis evaluates a software artefact, state the software version, environment, test data, defect or security criteria and baseline where relevant. A claim such as “the new system is more secure” needs measurable evidence, not only a design description.

30. Organisational recommendations are not automatically causal conclusions

An information system may be associated with better performance, user satisfaction or process outcomes without proving that the system caused the improvement. Be careful with words such as “impact,” “effect” and “improves” unless the design supports causal interpretation. Otherwise, describe associations, user evaluations, comparative results or observed patterns.

31. Personal-data planning must happen before processing

University data-protection guidance requires personal-data processing to be planned before it begins. Record the lifecycle in the research plan, address data protection and security, conduct risk assessment and consider a DPIA where applicable. Give research participants the required privacy information and collect only the data necessary for the academic objective.

32. Pseudonymised data may still be personal data

Replacing names with IDs does not automatically make data anonymous. If people can be re-identified from a key or combinations of variables, the data remain personal data. This is common in UX studies, employee research, software logs and organisational datasets. Keep re-identification information separate and restrict access according to the approved arrangement.

33. Ethics review depends on the actual project

Not every SEIS thesis needs formal ethics-committee review. However, projects involving human participants, sensitive data, interventions, deception or other applicable conditions may need preliminary ethical assessment. The University’s Human Sciences Ethics Committee handles relevant non-medical human-sciences requests. If review is needed, involve the supervisor and obtain it before the research activity that requires it.

34. Build a practical data-management plan

Responsible-research guidance expects planning for collection, storage, sharing, preservation and reproducibility. For an SEIS thesis, a useful data-management plan can include repositories, software versions, code branches, datasets, access rights, licences, data dictionaries, transformation logs, model configurations, output folders and retention or deletion decisions. Company data can remain closed while analytical provenance is still documented.

35. Research integrity includes code, datasets and AI-assisted work

Research integrity is not limited to plagiarism in prose. Technical theses can also misuse code, external repositories, datasets, generated text or AI-assisted analysis. Keep track of important external contributions and follow current University instructions for acknowledging AI use. A low similarity score does not prove that the methodology, data use or code attribution is correct.

36. The exact SEIS maturity test is II00BC92, 0 ECTS

Programme 52632 requires II00BC92 Maturity test for Master’s Degree, Software Engineering and Information Systems, carrying 0 ECTS and assessed PASS/FAIL. The current realization is II00BC92-3001. The exact course is more useful than maturity rules from another faculty because it describes the current SEIS implementation directly.

37. The maturity essay is about 500 words

The current II00BC92 course describes an approximately 500-word maturity essay. The text should be analytical and coherent and should present or analyse the research materials, methods and results. The thesis supervisor determines the title and evaluates the maturity text. The test is completed when the thesis is finalised or almost finished.

38. Some students can use the thesis abstract instead of a separate maturity essay

The exact SEIS course states that when the student does not need to demonstrate Finnish or Swedish language competence, the required Master’s thesis abstract can be accepted instead of writing a separate maturity text. The abstract still needs to demonstrate knowledge of the field. Do not copy the CSE maturity route or assume every student follows exactly the same language procedure.

39. Maturity-test language depends on the student’s case

The exact SEIS course lists Finnish or English, while University maturity rules depend on educational background and statutory language requirements. If the correct mode or language is unclear, verify it with the programme before completing the maturity requirement. A guide should not tell every international student to use English automatically.

40. Laturi submission must be public-safe

The current thesis process transfers approved theses to the University archive. Wider internet availability through OuluREPO depends on the student’s permission under current Laturi guidance, while other archive access remains available through designated University or library workstations. The final thesis must not contain secret trade or professional information. Resolve confidentiality before placing sensitive company details in the manuscript.

41. Plan graduation separately from thesis completion

After the thesis, maturity test and required studies are complete, degree application proceeds through Peppi. Current timetable information can change across the academic year, so check the live graduation page when planning the final date. A completed manuscript does not by itself mean that the degree can be granted immediately; examiner evaluation, committee handling, study completion and degree application all matter.

42. Final pre-submission checklist

Verify that II00BD01 remains the current 30 ECTS SEIS thesis, II00BC92 remains the current 0 ECTS maturity test, and 813627S remains optional rather than a compulsory extra thesis credit. Confirm supervisor and second-examiner arrangements, Laturi research-plan approval, SEIS-specific evaluation criteria, data and ethics permissions, reproducible analysis, public-safe company material, correct maturity route and current graduation timetable. Finally, recheck the curriculum boundary. The University is transitioning to the 2027-2030 curriculum, so current 2026-2027 thesis details should be freshly verified before they are treated as final rules for autumn-2027 study arrangements.