MPM_VIDA Data visualization

Faculty of Economics and Administration
Autumn 2020
Extent and Intensity
0/2/0. 5 credit(s). Type of Completion: z (credit).
Taught online.
Teacher(s)
Bc. Lukáš Havránek (lecturer)
Ing. Pavel Chlup (lecturer)
Guaranteed by
doc. Mgr. Maria Králová, Ph.D.
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
Timetable of Seminar Groups
MPM_VIDA/01: Wed 7. 10. 16:00–19:50 S310, Wed 21. 10. 16:00–19:50 S310, Wed 4. 11. 16:00–19:50 S310, Wed 11. 11. 16:00–19:50 S310, Wed 18. 11. 16:00–19:50 S310, Wed 2. 12. 16:00–19:50 S310, Wed 16. 12. 16:00–19:50 S310, Wed 6. 1. 16:00–19:50 S310, L. Havránek
Prerequisites
Subject require basic knowledge of work with computers and Microsoft excel.
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 24 student(s).
Current registration and enrolment status: enrolled: 0/24, only registered: 0/24, only registered with preference (fields directly associated with the programme): 0/24
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 using Tableau, the industry-leading software that provides reliable, 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 Tableau’s platform for visual 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 using visualizations in Tableau 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
  • Week 1 - Introduction to visualization Installing data analysis and visualization software (tableau desktop, tableau Prep, and Tableau Server) Week 2 - Tebleau Prep with Text and Excel Files basics of working with data - reading data from various formats, reading data from databases, editing, cleaning and storing source data, linking data based on primary keys LEFT, RIGHT, INNER and OUTER join. Data aggregation. Week 3 - The Tableau User Interface Basics of working in Tableau desktop Week 4 - Discrete + Continuous Time series processing Week 5 - Basic Charts Basic charts and their effective use - Column charts, area charts, Cross tabs, Geographic maps, Heat maps, Scatterplots, Piecharts, Treemaps, Biaxial diagrams Week 6 - Dashboards and Stories Methods of presentation visualization in Tableau Desktop Week 7 - Formatting Basics tableau output formatting Week 8 - Intro to Calculated Fields Introduction to Key Indicators, Indicators and Decision Triggers, Key Performance Indicators (KPIs), Spreadsheet Calculations and KPIs, Creating Complex KPIs Using Tables Week 9 - Intro to Maps - work with geographic data editing coordinates in Tableau linking data of municipalities in the Czech Republic with the program. Dual maps - business traveler problem Edit Week 10 - Connection to PDF, Pareto Chart and Control Chart Basics of industrial data analysis - Pareto graph and control charts Week 11 - Market Basket Matrix Week 12 - Waterfall Week 13 - Credit test
Literature
    recommended 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
Teaching methods
The course consists of exercises. Students have to bring their own laptops on which they will be added to the license of program Tableau.
Assessment methods
The course is evaluated on the basis of attendance (10%), in-class tests (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 obtainint 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. Communication with living people by all means is prohibited. • Any copying, recording or taking out the tests, use of unauthorized devices and means of communication or other distortions objectivity test (credit) will be considered a failure to meet the course completion and a gross violation of study regulations. Consequently, the teacher closes the test (credit) score in IS grade "F" and Dean initiate disciplinary proceedings which may result in up to graduation.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Autumn 2017, Autumn 2018, Autumn 2019.
  • Enrolment Statistics (recent)
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