Course detail

Information Processing

FSI-BZIAcad. year: 2017/2018

The course provides an introduction to information processing. It deals with the following topics: data acquisition and sensors, data organisation, data processing in database systems, DBS architecture, relations and data models, fundamentals of SQL (Structured Query Language), data analysis using spreadsheets and advanced math software, proper presentation of data using charts, graphics and reports.

Learning outcomes of the course unit

The course familiarises students with theoretical and practical aspects of data processing. It will provide them with tools necessary for efficient selection of solutions for data acquisition, database and presentation applications.


Successful completion of the course "Information Processing" is conditional on basic knowledge of common IT usage, as tought on secondary schools. Lectures may be partialy based on 1IN topics, taught at winter semester.


Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Date, C.J.: An Introduction to Database Systems. Addison Wesley, New York, 2003 (8th edition).
Pokorný, J., Halaška, I.: Databázové systémy.
Fortier, P.J.: Database Systems Handbook. McGraw-Hill, 1997.
Pokorný, J.: Visual Basic pro aplikace Accessu 2000.
Date, C.J.: An Introduction to Database Systems. Addison Wesley, New York, 2003 (8th edition).
Lacko, L.: SQL. Hotová řešení pro SQL Server, Oracle a MySQL. Computer Press, Brno, 2003.
Pokorný, J.: Konstrukce databázových systémů. Skriptum ČVUT FEL, Praha, 1999.
Pokorný, J.: Visual Basic pro aplikace Accessu 2000. Kopp, České Budějovice, 2000.
Viescas, J.: Mistrovství v Microsoft Access 2000. Computer Press, Praha, 2000.

Planned learning activities and teaching methods

The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures. Teaching is suplemented by practical laboratory work.

Assesment methods and criteria linked to learning outcomes

The course-unit credit is awarded on condition of attendance in seminars and having passed the given tasks and tests.
All the above defined tasks are awarded with 0 or 1 points, while the total sum is a decisive parameter for granting the course credits. The percentual requirement for automatically granted credists is set to 71% of available points, related to final number of excused absence.
Repeated unpreparedness (3 or more failed tests in line or less than 50% points) and/or unexcused absence are contradictory to successfull course completion.

Language of instruction


Work placements

Not applicable.


The course aims to acquaint the students with basic methods of work with technical data and usage of computers, required for praxis of nowadays mechanical engineers.

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

Since the quallified attendance at seminars is required, it will be checked regularly by the seminar teacher, using e-learning quiz tests. All important sources shall be regularly available at e-learning and colnsultation hours, unpreparedness at computer laboratory may disqualify students from completing the topic.
In case of absence (but not more than 2 consecutive lectures and not more than 2 unexcused absences), an individual written semestral work may be required to receive course credits.

Classification of course in study plans

  • Programme B3A-P Bachelor's

    branch B-PDS , 1. year of study, summer semester, 4 credits, compulsory

  • Programme B3S-P Bachelor's

    branch B-S1R , 1. year of study, summer semester, 4 credits, compulsory

Type of course unit



26 hours, optionally

Teacher / Lecturer


1. Introduction, data and information, data types in IT, data acquisition in mechanical engineering, classes of electronic sensors.
2. Historical and contemporary data transport methods, principles of modulation and data encoding - protection, encryption, compression.
3. Data storage solutions, file format function, basic data formats and architectures, data structures and methods of work with heterogenous data.
4. Sequential data access - sorting and filtering, principles of relational database function and data normalization.
5. Problematics and solutions for data redundancy and inconsistency in multi-user data access, files and distributed databases, reasons for client-server schema of work, database definition and manipulation languages and a common database application interfaces.
6-7. SQL: Selections, ordering, aggregations, unions, output transformation, sub-queries, basic action and data definition queries.
8. Spreadsheets: reasons for work with tabular data, usage of formulas on data in order to obtain the required information, analytical tools, common principles of preparation of textual and graphical outputs.
9. All-in-one data processing in LabVIEW.
10. All-in-one data processing in Matlab.
11. Technical documents - basic typographic rules, importance of implicit styles and other advanced functions in modern text editors, graphics in technical documents.
12. Presentation of results - proper order of technical documents, information reliability (discussion of results, proper citations), differences between printed technical documents, posters and presentations.
13. Finalization of course.

Computer-assisted exercise

22 hours, compulsory

Teacher / Lecturer


1-2. LabVIEW principles
3-4. ÚAI laboratories: Electronical sensors for data acquisition, industrial data acquisition using PLC and PC
5. Principles of data transfer, encoding and encryption
6. Microsoft Access - desktop database environment introduction, creation of data tables
7. Microsoft Access - relational databases in access
8. Microsoft Access - SQL
9. Microsoft Access - User Applications, VBA
10. Data analysis using spreadsheets – formulas, sorting, pivot tables, charts
11. Creation of complex text documents
12-13. Reserved for advanced topics and consultation of course credits.

labs and studios

4 hours, compulsory

Teacher / Lecturer


1. Practical examples of data acquisition hardware, including relevant PC and PLC Software.