A course is the basic teaching unit, it's design as a medium for a student to acquire comprehensive knowledge and skills indispensable in the given field. A course guarantor is responsible for the factual content of the course.
For each course, there is a department responsible for the course organisation. A person responsible for timetabling for a given department sets a time schedule of teaching and for each class, s/he assigns an instructor and/or an examiner.
Expected time consumption of the course is expressed by a course attribute extent of teaching. For example, extent = 2 +2 indicates two teaching hours of lectures and two teaching hours of seminar (lab) per week.
At the end of each semester, the course instructor has to evaluate the extent to which a student has acquired the expected knowledge and skills. The type of this evaluation is indicated by the attribute completion. So, a course can be completed by just an assessment ('pouze zápočet'), by a graded assessment ('klasifikovaný zápočet'), or by just an examination ('pouze zkouška') or by an assessment and examination ('zápočet a zkouška') .
The difficulty of a given course is evaluated by the amount of ECTS credits.
The course is in session (cf. teaching is going on) during a semester. Each course is offered either in the winter ('zimní') or summer ('letní') semester of an academic year. Exceptionally, a course might be offered in both semesters.
The subject matter of a course is described in various texts.

ANI-EDM	Enterprise Data Management			Extent of teaching:	2P+1C
Instructor:	Valenta M.			Completion:	Z,ZK
Department:	18102	Credits:	5	Semester:	L

Annotation:
Předmět poskytne studentům praktický přehled o tom, jak velké organizace zpracovávají, ukládají a využívají data. Cílem je seznámit studenty zejména s moderními přístupy ke správě dat (Data Management), návaznostem na podnikovou a IT architekturu a také technologiím pro zpracování podnikových dat a metadat, včetně prostředků strojového učení a umělé inteligence. Důraz bude kladen na reálné příklady z praxe a získání informací využitelných v podnikové sféře. Oblast zpracování dat a datových technologií je mimořádně dynamická, a proto bude obsah předmětu průběžně přizpůsobován aktuálním trendům a nejnovějším poznatkům z praxe tak, aby studenti získali co nejrelevantnější dovednosti pro moderní prostředí velkých organizací.

Lecture syllabus:

1.		The importance of data in large company. Role of data in a modern company. Manager and machine strategic decision-making.
2.		Relationship of data architecture to other pilies of business architecture. Business layer of Data Management (DM).
3.		(2) Data architecture. Data intensive application and data landscape.
4.		Master Data Management. Traditional and historical approaches to Data Management.
5.		Classic data processing and Business Intelligence. Data warehouses, analyses and reporting.
6.		Modern corporate data platform as a three-lane highway. First speed bar - classic data warehouse, centralization, one version of truth.
7.		Second speed lane - decentralization and democratization of data, business ownership, data products and concept of Data Mesh.
8.		Third speed lane - DataOps - operation, integration, MLOPS.
9.		Advanced analyses and involvement of artificial intelligence.
10.		Role of data science in companies. Data Management as a multidisciplinary field. Introduction to CRISP-DM methodology.
11.		Proces správy dat. Fáze ostrého-DM, jeho iterativní povaha. Správa a statistika dat.
12.		Strojové učení. Aplikace AI při řešení úkolů správy dat.

Seminar syllabus:
bude doplněno

Literature:

1.		Piethein Strengholt: Data Management at Scale: Best Practices for Enterprise Architecture 1st Edition. O'Reilly Media, 2020. ISBN 978-1492054788.
2.		Dave Knifton: Enterprise Data Architecture: How to navigate its landscape. Paragon Publishing, 2014. ISBN 978-1782223269.

Requirements:

Výukové materiály na https://courses.fit.cvut.cz

The course is also part of the following Study plans:

Study Plan Study Branch Role Recommended semester QNI Unspecified Specialisation of Study V 2 ANI-WI Web Engineering VO 2 ANI-SI Software Engineering (in Czech) VO 2 NI-PB.2026 Computer Security V 2 NI-SPOL.2026 Unspecified Specialisation of Study V 2 NI-UI.2026 Artificial Intelligence V 2 NI-PJ.2026 Programming Languages V 2 NI-TI.2026 Computer Science V 2 NI-PSS.2026 Computer Systems and Networks V 2 ANI-ES Embedded systems VO 2 ANI-MI Business Informatics VO 2 ANI-VG Visual computing and Game design VO 2 ANI-SI Software Engineering (in Czech) PS 2 ANI-SPOL Unspecified Specialisation of Study VO 2 ANI-MI Business Informatics PS 2

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Page updated 18. 8. 2026, semester: Z/2023-4, Z/2021-2, Z/2022-3, L/2025-6, L/2022-3, Z/2025-6, L/2023-4, L/2024-5, Z/2026-7, L/2021-2, L/2026-7, Z/2024-5, Send comments to the content presented here to Administrator of study plans

Design and implementation: J. Novák, I. Halaška