Data-driven Management
BASIC DATA
course listing
A - main register
course code
MMK3110
course title in Estonian
Andmepõhine juhtimine
course title in English
Data-driven Management
course volume CP
-
ECTS credits
6.00
to be declared
yes
fully online course
not
assessment form
Examination
teaching semester
autumn
language of instruction
Estonian
English
Study programmes that contain the course
code of the study programme version
course compulsory
yes
Structural units teaching the course
MM - Department of Business Administration
Timetable link
Version:
VERSION SPECIFIC DATA
course aims in Estonian
Aine eesmärk on arendada teadmisi, oskusi ja hoiakuid andmepõhise juhtimise valdkonnas ning omandada ärianalüütika baaslähenemised lihtsamate ärirakenduste tasemel.
course aims in English
The aim of this course is to develop knowledge, skills and attitudes relevant to the concept of data-driven management and to develop skills in business intelligence on the level of Basic business applications.
learning outcomes in the course in Est.
Õppeaine läbinud üliõpilane:
- analüüsib andmepõhise juhtimise ja ärianalüütika aluskontseptsioone, põhimõtteid ning meetodeid ja nende omavahelisi seoseid;
- kirjeldab kaasaegseid andmete kogumise, andmeanalüüsi ja visualiseerimise võimalusi ning andmete ja faktide rolli juhtimisotsuste langetamisel;
- kasutab eesmärgipäraselt lihtsamaid ärianalüütika tehnilisi lahendusi.
- analüüsib andmepõhise juhtimise ja ärianalüütika aluskontseptsioone, põhimõtteid ning meetodeid ja nende omavahelisi seoseid;
- kirjeldab kaasaegseid andmete kogumise, andmeanalüüsi ja visualiseerimise võimalusi ning andmete ja faktide rolli juhtimisotsuste langetamisel;
- kasutab eesmärgipäraselt lihtsamaid ärianalüütika tehnilisi lahendusi.
learning outcomes in the course in Eng.
After completing this course, the student:
- analyses the foundational concepts, principles and methods of data-driven management and business analytics and respective relationships;
- describes contemporary applications of data collection, data analysis and visualization and the role of data and facts in making business decisions;
- uses purposefully relevant basic solutions of business intelligence.
- analyses the foundational concepts, principles and methods of data-driven management and business analytics and respective relationships;
- describes contemporary applications of data collection, data analysis and visualization and the role of data and facts in making business decisions;
- uses purposefully relevant basic solutions of business intelligence.
brief description of the course in Estonian
Andmepõhine juhtimine. Ärianalüütika olemus. Andmed. Kirjeldav analüütika. Korrelatsioon ja lineaarne regressioon. Andmeanalüütika strateegiline kasutamine äriliste küsimuste lahendamisel. Mudelid, visualiseerimine ja juhtimislauad. Andmete jagamine. Andmevarustamine. Relatsiooniline andmemudel ja andmebaasid. Visuaalne analüütika. Ärianalüüsi protsess. Andmelaod ja andmeaidad. Andmekaeve. Andmekirjaoskus ja andmepõhinekultuur ettevõttes. Tulevikutrendid.
brief description of the course in English
Data-driven management. The nature of business intelligence. Data. Descriptive analytics. Correlation and linear regression. Strategic use of business intelligence in making business decisions. Models, visualization and dashboards. Data sharing. Relational data modelling and databases. Visual Analytics. The process of business analytics. Data warehousing concepts. Data mining. Data literacy and data-driven culture in the company. Future trends.
type of assessment in Estonian
Täpsustatud laiendatud ainekavas.
type of assessment in English
Shall be specified in extended syllabus.
independent study in Estonian
-
independent study in English
-
study literature
Sharda et al. Business Intelligence, Analytics and Data Science. A Managerial Perspective (Pearson, 2017).
Laursen and Thorlund. Business Analytics for Managers: Taking Business Intelligence Beyond Reporting (Wiley, 2017).
Laursen and Thorlund. Business Analytics for Managers: Taking Business Intelligence Beyond Reporting (Wiley, 2017).
study forms and load
daytime study: weekly hours
3.0
session-based study work load (in a semester):
lectures
1.0
lectures
-
practices
0.0
practices
-
exercises
2.0
exercises
-
lecturer in charge
-
LECTURER SYLLABUS INFO
semester of studies
teaching lecturer / unit
language of instruction
Extended syllabus
Course-teacher pairs of the corresponding version are missing!