155-1336/01 – Data Analysis in MS Office 365 (ADMO)

Gurantor departmentDepartment of Applied InformaticsCredits4
Subject guarantorIng. Vítězslav Novák, Ph.D.Subject version guarantorIng. Vítězslav Novák, Ph.D.
Study levelundergraduate or graduateRequirementChoice-compulsory type B
Year2Semestersummer
Study languageCzech
Year of introduction2022/2023Year of cancellation
Intended for the facultiesEKFIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
NOV21 Ing. Vítězslav Novák, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Graded credit 1+2

Subject aims expressed by acquired skills and competences

The aim of the course is to familiarize students with the possibilities of Microsoft Excel spreadsheet for data analysis. The show will be applicable to the basic fuctions and advanced tools such as structured tables, pivot tables, Power Query tool for data transformations and Power Pivot add-in for managing data models. The Power BI tool for data visualization and report creation will also be presented.

Teaching methods

Lectures
Tutorials
Project work

Summary

The aim of the course is to familiarize students with the possibilities of Microsoft Excel spreadsheet for data analysis. The show will be applicable to the basic fuctions and advanced tools such as structured tables, pivot tables, Power Query tool for data transformations and Power Pivot add-in for managing data models. The Power BI tool for data visualization and report creation will also be presented.

Compulsory literature:

WINSTON, Wayne. Microsoft Excel Data Analysis and Business Modeling (Office 2021 and Microsoft 365). San Francisco, Microsoft Press, 2021. ISBN 978-0137613663. ALEXANDER, Michael and KUSLEIKA, Dick. Microsoft Excel 365 Bible. Indianapolis, John Wiley & Sons, 2022. ISBN 978-1119835103. DECKLER, Greg and POWELL, Brett. Mastering Microsoft Power BI - Second Edition: Expert techniques to create interactive insights for effective data analytics and business intelligence. Birmingham, Packt Publishing, 2022. ISBN 978-1801811484.

Recommended literature:

FERRARI, Alberto and Marco RUSSO. Analyzing Data with Microsoft Power BI and Power Pivot for Excel. Redmond, Washington: Microsoft Press, 2017. ISBN 978-1-5093-0276-5. RUSSO, Marco and Alberto FERRARI. The Definitive Guide to DAX: Business Intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel Second Edition. Redmond, Washington: Microsoft Press, 2019. ISBN 978-1509306978. DECKLER, Greg. Learn Power BI - Second Edition: A comprehensive, step-by-step guide for beginners to learn real-world business intelligence. Birmingham, Packt Publishing, 2022. ISBN 978-1801811958.

Way of continuous check of knowledge in the course of semester

Classified credit: - test: data analysis in Excel. - project in Power BI.

E-learning

Students have all presentations, assignments and exercises data in LMS Moodle.

Other requirements

Knowledge of the basics of MS Excel at the level of the Informatics subject in the 1st year of bachelor's studies. Active participation in exercises. Elaboration and defense of project with respect to the required structure. Inserting this project into the LMS Moodle and obtaining a simple majority of the number of points.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1) Excel – repeating the necessary basics 2) Excel – work with lists 3) Excel – data analysis using formulas 4) Excel – data analysis using structured tables 5) Excel – data analysis using pivot tables and charts 6) Excel – data analysis using the Power Pivot add-on and the DAX language 7) Excel – data import and transformation using Power Query 8) Power BI – the philosophy of the tool 9) Power BI – creating reports in Power BI Desktop 10) Power BI – DAX language in Power BI 11) Power BI - relationships 12) Power BI – Power Query in Power BI

Conditions for subject completion

Full-time form (validity from: 2023/2024 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)		Min. number of pointsMax. počet pokusů
Graded credit Graded credit 100  51 3
Mandatory attendence participation: Credit: - attendance at the seminars is not required, - successfully completed test, - processing of project according to the required structure and submission in LMS Moodle.

Show history

Conditions for subject completion and attendance at the exercises within ISP: Credit: - attendance at the seminars is not required, - successfully completed test, - processing of project according to the required structure and submission in LMS Moodle.

Show history

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Occurrence in special blocks

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Assessment of instruction

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