BKM_VIBD Business Data Visualization

Faculty of Economics and Administration
Autumn 2022

The course is not taught in Autumn 2022

Extent and Intensity
0/0/0. 6 credit(s). Type of Completion: z (credit).
Teacher(s)
Ing. Pavel Chlup (lecturer)
Guaranteed by
Ing. Pavel Chlup
Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Contact Person: Lenka Hráčková
Supplier department: Department of Applied Mathematics and Computer Science – Faculty of Economics and Administration
Prerequisites
Subject require basic knowledge of work with computers and Microsoft excel.
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The ability to characterize and communicate practical implications of quantitative analyses to any kind of audience member is the hallmark of great data analysts. The richest data is useless to any enterprise if it fails to result in actionable advice, or if the advice does not convey solutions and directions in a way that all stakeholders can understand. Learn how to become a master at communicating business-relevant implications of data analyses. Flexible, and repeatable methods for analyzing real-world data. This course investigates visual analytics and related concepts with Tableau through the completion of real-world case studies. Learn in detail how to use visualization software for analysis and business intelligence, which will help you to see and understand data like never before. Acquire the skills in Tableau to connect to multiple data sources, enhance them, and display them using visual analysis techniques. The goal of this course is to provide students The ability to structure data analysis projects so that they can provide maximum impact to all stakeholders. Experience streamlining analyses and highlighting implications efficiently. The skills to make effective visualizations that convey conclusions directly and clearly.
Learning outcomes
Completing the course, students will gain the following skills: read data from various formats, read data from databases, edit, clean and save source data, link data based on primary keys LEFT, RIGHT, INNER and OUTER join. Students will be able to create: Bar Graphs, Area Graphs, Cross Tabs, Geographic Maps, Heat Maps, Scatterplots, Piecharts, Treemaps, Interactive Dashboards and Stories. create calculation tables, work with parameters, create calculation fields, export results and present results. work with time series, understand aggregation, granularity and level of detail, add filters and quick filters, create data hierarchies.
Syllabus
  • 1. Introduction: installation of data analysis and visualization software, data basics - loading data from various formats, loading data from databases, editing, cleaning and saving source data, linking data based on primary keys LEFT, RIGHT, INNER and OUTER join . Data aggregation. 2. Basic graphs and their effective use, work with time series Scatterplots, Biaxial diagrams, Dashboards and Stories - Introduction to Key Indicators, Indicators and Decision Triggers, Key Performance Indicators (KPIs), Spreadsheet Calculations and KPIs, Creating Complex KPIs Using Tables 3. Creation of calculated fields, work with geographic data - business traveler problem, dual maps.Market Basket Matrix, Waterfall. Basis of industrial data analysis - pareto graph and control charts
Literature
    required literature
  • MURRAY, Dan. Tableau your data! : fast and easy visual analysis with tableau software . Indianapolis, Indiana: Wiley, 2013. 528 s. ISBN: 978-1-118-61204-0
    recommended literature
  • KNAFLIC, Cole Nussbaumer. Storytelling with data : a data visualization guide for business professionals. Hoboken, New Jersey: Wiley, 2015, xiii, 267. ISBN 9781119002253. info
  • FEW, Stephen. Show me the numbers : designing tables and graphs to enlighten. Second edition. El Dorado Hills, California: Analytics Press, 2012, xviii, 351. ISBN 9780970601971. info
  • TUFTE, Edward R. The visual display of quantitative information. Second edition. Cheshire: Graphics Press, 2001, 197 s. ISBN 9780961392147. info
Teaching methods
The course consists of practically oriented tutorials studying recommended sources and individual work on a project. Students have to bring their OWN laptops which will be associated with access and the license for Tableau.
Assessment methods
The course is evaluated on the basis of attendance (10%), Homework (30%), projects (30%) and a final practical exam (30 %). Homework and final practical exam include preparation, analysis, and visualization of given data. The successful completion of the course requires obtaining at least 50% of points from the final exam and 50% of the total possible points. • During the test, it is possible to use all materials available in IDE, Internet, and personal notes.
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: in blocks.
Note related to how often the course is taught: 12 hodin.
Information on the extent and intensity of the course: tutorial 12 hodin.
The course is also listed under the following terms Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2022, recent)
  • Permalink: https://is.muni.cz/course/econ/autumn2022/BKM_VIBD