Course detail

Data Processing

FP-zdPAcad. year: 2022/2023

The course is understanding the nature of the data from various sources and to gain knowledge allowing them to analyze and process skills, including presentation in an appropriate form for management decision support.

Language of instruction

Czech

Number of ECTS credits

4

Mode of study

Not applicable.

Guarantor

Ing. Jiří Kříž, Ph.D.

Department

Institute of Informatics (ÚI)

Learning outcomes of the course unit

Learning outcomes - general competencies:
The skills associated with the use and treatment of information.
The ability of analysis and synthesis, application knowledge in practice, solve problems independently
Industry-specific competencies:
Students understand the principles of data acquisition, gain knowledge of data processing in information systems and their adaptation for presentation.

Prerequisites

Knowledge of working with MS Office.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

The course contains lectures that explain basic principles, problems and methodology of the discipline, and exercises that promote the practical knowledge of the subject presented in the lectures.

Assesment methods and criteria linked to learning outcomes

Completion of the subject

Credit conditions: During the semester, the student must obtain at least 50% of the possible maximum points, i.e. 50 points out of 100. If plagiarism or illegal collaboration on projects or on the mid-semester test is detected, the credit will not be granted with the possibility of considering the initiation of disciplinary proceedings. Mid-semester test - preparation of a practical task according to the assignment with a focus on obtaining data from databases. There is no correction deadline. (max. 30 points).

Development of the project - one project according to the assignment with relevant documentation. Students are introduced to the assignment in the third lecture. (max. 70 points). Submission and defense of the project in the credit week.

Completion of the subject for students with individual study:

Development of the project - one project according to the assignment with relevant documentation. The assignment will be published in e-learning from the third week of the semester.

Course curriculum

The course focuses on the principles and methods of data collection and processing in information systems and their adaptation for presentation.

Topics of the lectures:
Character data from various sources, search options
Database tables, attributes, data types
Handling tables and records, views and reports
Working with data in MS Excel
Power Pivot, data analysis tool
Decision support systems
Data aggregation and analysis (OLAP)

The workout is required continuous training, exercises are designed to process jobs based on the source data files and results presentation.

Work placements

Not applicable.

Aims

The aim is understanding the nature of the data from various sources and to gain knowledge allowing them to analyze and process skills, including presentation in an appropriate form for management decision support.
Learning outcomes - general competencies:
The skills associated with the use and treatment of information.
The ability of analysis and synthesis, application knowledge in practice, solve problems independently
Industry-specific competencies:
Students understand the principles of data acquisition, gain knowledge of data processing in information systems and their adaptation for presentation.

Specification of controlled education, way of implementation and compensation for absences

Attendance at lectures is not compulsory. Computer-aided exercises are compulsory, attendance is monitored. One of absence from seminars, teacher apologize. Student replace this lack of elaboration specifically assigned homework.

During the semester, written semester test for a maximum of 20 points. For this semester test, there is no retake. If a student is properly documented and teacher excused absence just in lessons, where he writes a midterm exam, you may report it to the alternative.

In the second lecture is given to students separate project for a maximum of 20 points. So this project was recognized for his student must obtain a minimum. 10 points. Student submits a project in the credit week.
Students who have Individual Study Plan, ie. They do not go into teaching for the credit must develop and submit a separate stand-alone project. For this particular project can get max. 30 points.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

KŘÍŽ, J. Zpracování dat. Učební text. VUT v Brně, fakulta podnikatelská.(bude vydáno v září 2015).
BARILLA, J. Microsoft Excel 2013 :podrobná uživatelská příručka. Brno: Computer Press, 2013. 1. vyd. 496 s. ISBN 978-80-251-4114-4.

Recommended reading

CONOLLY, T., C. BEGG a R. HOLOWCZAK. Mistrovství – Databáze : Profesionální průvodce tvorbou efektivních databází. 1.vyd. Brno: Computer Press, 2009. 584 s. ISBN 978-80-251-2328-7.
LACKO, L. Jak vyzrát na SQL Server 2008. Brno: Computer Press, 2009. 469 s. ISBN 978-80-251-2101-6.

Classification of course in study plans

  • Programme BAK-PM Bachelor's, 1. year of study, summer semester, compulsory
  • Programme BAK-UAD Bachelor's, 2. year of study, summer semester, compulsory-optional
  • Programme BAK-EP Bachelor's, 2. year of study, summer semester, compulsory-optional

Type of course unit

 

Lecture

13 hours, optionally

Teacher / Lecturer

Ing. Jiří Kříž, Ph.D.

Syllabus

Na cvičení je vyžadována průběžná příprava, cvičení jsou zaměřena na zpracování úloh založených na zdrojových datových souborech a prezentaci výsledků.

Exercise

26 hours, compulsory

Teacher / Lecturer

Ing. Dita Kindlová
Ing. Lukáš Václavík