Materials focused on effective data visualization in MS Excel and Tableau. Examples are based on real Ukrainian and international datasets.
Language of course:
Ukrainian
Format of the event:
Video lectures
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Course overview
Description generated based on course syllabus and open data.
These materials focus on effective data visualization in MS Excel and Tableau. The set includes 9 concise videos, 5 slide decks, and all datasets used in the examples, including large collections with over 200,000 records from Ukrainian and international sources.
Examples cover charts, graphs, maps, dashboards, and data preparation techniques that support transparent analysis and fair comparisons.
Who it suits / who it doesn't for data visualization in MS Excel and Tableau
Suitable for
- Analysts and researchers working with tabular data and reports.
- Professionals needing informative charts and dashboards without coding.
- Students and educators using real Ukrainian and international data.
Not suitable for
- Those seeking automation in Python/R or advanced ETL.
- Users requiring an enterprise BI platform with server deployment.
Problem → outcome in the context of effective data visualization
Problems
- Overloaded charts without visual hierarchy.
- Unreadable scales, labels, and legends.
- Large datasets (200k+) with inconsistent formats.
Target outcome of the materials
- Clear charts and dashboards with consistent labels and colors.
- Proper comparisons and filtering in Excel and Tableau.
- Reproducible visualization steps on large datasets.
Comparison with alternative visualization tools
- Power BI: similar dashboard logic; Excel/Tableau fit when XLSX compatibility or offline work is important.
- Google Looker Studio: easy web sharing; Excel/Tableau provide finer formatting and interaction control.
- Python/R (matplotlib, ggplot2): code flexibility; Excel/Tableau suit fast visual analysis without programming.
Learning content outcomes with MS Excel and Tableau
- Building line, bar, combo charts, maps, and heatmaps.
- Creating dashboards with filters, highlights, and labels.
- Data preparation: cleaning, aggregation, sorting, formatting.
- Evaluating visual choices: scales, colors, markers, legends.
- Replicating examples on datasets with over 200k records.
Course Description
You will have access to 9 short informative videos, 5 presentations and all the data used in this course. Therefore, you will be able to fully reproduce all our visualizations based on real Ukrainian and international data, including large arrays with more than 200 thousand observations.
Evaluation
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