ESF:MPM_VIDA Data visualization - Course Information

MPM_VIDA Data visualization

Extent and Intensity

0/2/0. 5 credit(s). Type of Completion: z (credit).

Teacher(s)

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: Mon 16:20–17:55 S313, P. Chlup

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: Connect Tableau to various Datasets: Excel and CSV files;Create Barcharts;Create Area Charts;Cross tabs;Geographic maps;Heat maps;Create Scatterplots;Create Piecharts;Create Treemaps;Create Interactive Dashboards;Create Storylines;Understand Types of Joins and how they work;Work with Data Blending in Tableau;Create table Calculations;Work with Parameters;Create Dual Axis Charts;Create Calculated Fields;Create Calculated Fields in a Blend;Export Results from Tableau into Powerpoint, Word, and other software Work with Timeseries Data;Creating Data Extracts in Tableau Understand Aggregation, Granularity, and Level of Detail Adding Filters and Quick Filters.

Syllabus

• 1. Introduction to Tableau: program installation, Tableau terminology, edit and save a data source, connecting Tableau to a Data File - CSV File, Navigating Tableau, Creating Calculated Fields, Adding Colors, Adding Labels and Formatting, Exporting Your Worksheet, • 2. Time series, Aggregation, and Filters, Working with Data Extracts in Tableau, Working with Time Series, Understanding Aggregation, Granularity, and Level of Detail, Creating an Area Chart & Learning About Highlighting, Adding a Filter and Quick Filter • 3. Maps, Scatterplots, First Dashboard Joining Data in Tableau, Creating a Map, Working with Hierarchies, Creating a Scatter Plot, Applying Filters to Multiple Worksheets, Adding an Interactive Action - Filter, Adding an Interactive Action - Highlighting • 4. Joining and Blending Data, PLUS: Dual Axis Charts, Understanding how LEFT, RIGHT, INNER, and OUTER Joins Work, Joins With Duplicate Values, Joining on Multiple Fields, The Showdown: Joining Data v.s. Blending Data in Tableau, Data Blending in Tableau, Dual Axis Chart, Creating Calculated Fields in a Blend (Advanced Topic) • 5. Introduction to Key Metrics, Indicators, and Decision Triggers, Key Performance Indicators (KPIs), Tableau Calculated Fields and KPIs, Creating Complex KPIs Using Tableau, Thresholds and Alerts, Data Quality • 6. Table Calculations, Downloading the Dataset and Connecting to Tableau, Mapping: how to Set Geographical Roles, Creating Table Calculations for Gender, Creating Bins and Distributions For Age, Leveraging the Power of Parameters, How to Create a Tree Map Chart • 7. Advanced Dashboards, Creating a Customer Segmentation Dashboard, Advanced Dashboard Interactivity, Analysing the Customer Segmentation Dashboard • 8. Framing and Format, Framing, Conventions, and Priming, Single-Frame Visualization • 9. Storytelling, Creating a Storyline, Prioritizing, Optimizing, and Designing the Data Story, Create a Data Story in a Static Presentation • 10. Advanced Data Preparation, What Format Your Data Should Be In, Data Interpreter, Pivot, Splitting a Column into Multiple Columns, MetaData Grid, Fixing Geographical Data Errors in Tableau • 11. Custom Territories Via Groups, Custom Territories Via Geographic Roles, Adding a Highlighter • 12. Clustering In Tableau, Cross-Database Joins, Modeling With Clusters, Saving Your Clusters • 13. New Design Features, Single Frame Visualizations, Examples of Multi-Frame Data Stories

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 (probably available only in Czech)

Study Materials
The course is taught annually.

• Enrolment Statistics (Autumn 2017, recent)
  
• Permalink: https://is.muni.cz/course/econ/autumn2017/MPM_VIDA