PV250 Marketing Information Systems

Faculty of Informatics
Autumn 2017

The course is not taught in Autumn 2017

Extent and Intensity
2/1/0. 3 credit(s) (plus extra credits for completion). Recommended Type of Completion: k (colloquium). Other types of completion: z (credit).
Teacher(s)
Dalia Kriksciuniene, Ph.D. (lecturer), Ing. Leonard Walletzký, Ph.D. (deputy)
prof. RNDr. Tomáš Pitner, Ph.D. (lecturer)
Ing. Leonard Walletzký, Ph.D. (assistant)
Guaranteed by
doc. RNDr. Eva Hladká, Ph.D.
Department of Computer Systems and Communications – Faculty of Informatics
Supplier department: Department of Computer Systems and Communications – Faculty of Informatics
Course Enrolment Limitations
The course is offered to students of any study field.
Course objectives
The module is aimed to provide advanced interdisciplinary knowledge and augmented skills for creating enterprise information systems able to support marketing management processes and to provide information, which could meet the needs of marketing management specialists. The teaching module introduces creation principles and variety of concepts used for building marketing information systems (MkIS). The course provides knowledge of the functional components and structure of MkIS, develops ability to distinguish and apply methods of marketing management, including marketing planning, modelling and customer relationship management domains. The students get acquainted and acquire practical skills of marketing analytics by using intelligent computational tools, cloud-based applications, functional modules of the integrated systems, market games, and applied software for marketing decision-making, planning and control. The module also aims to deepen scientific writing skills and apply methods of virtual team learning for fulfilment of assignments in MkIS area.
Syllabus
  • Definitions, functions, requirements for the marketing information systems (MKIS). The users of marketing information, their requirements for the information content, inputs, retrieval and presentation. Investigation of the scientific and experimental research in MKIS area in the scientific literature. Types and functions of the information systems, their usage for the marketing purposes: operational, analytical, OLAP, expert, executive, decision-support systems. Applying ERP, business intelligence, integrated software for marketing tasks. Marketing planning, process modelling and decision making by using MKIS. Tools and processes of the marketing manager: analytical and control applications: pivot tools, dashboards, computational intelligence methods for marketing, multi-stage market modeling games. CRM performance analysis: CRM analytical methods; computational intelligence methods: neural networks, fuzzy rules, Kohonen self organizing networks. Cloud based and open source solutions.
Literature
    recommended literature
  • Data mining techniquesfor marketing, sales, and customer relationship management. Edited by Gordon S. Linoff - Micahel J. A. Berry. 3rd ed. Indianapolis, Ind.: Wiley Pub., Inc., 2011, xl, 847 p. ISBN 9781118087503. info
Teaching methods
Lectures, seminars, lab work training, problem-based learning, case analysis, task solving in teams by using distant learning methods, acquiring hands-on skills on operational and analytical software.
Assessment methods
The two options of completion imply the following assessment methods: z (3 credits- course completion) – final test and course assignments submitted and defended; k (3+1 –completion with colloquium) – final test and all course assignments submitted and defended, the scientific paper prepared according to the requirements for inclusion to the scientific conference for Master and Doctoral students.
Language of instruction
English
Further comments (probably available only in Czech)
Study Materials
The course is taught once in two years.
The course is taught: in blocks.
The course is also listed under the following terms Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2018, Autumn 2019, Autumn 2022, Autumn 2023.
  • Enrolment Statistics (Autumn 2017, recent)
  • Permalink: https://is.muni.cz/course/fi/autumn2017/PV250