Taxation had always been an issue of great interest in Greece, so here is a cool and interesting analysis on Greek Tax Data  with SAP Lumira.

The data came from the open data of the General Secretariat of Information Systems (

In this post you can see the 1st part of this analysis, and later a second one will follow with the rest of it. Here is the 2nd part–greek-tax-data-analysis-part-2.

Through this extent analysis, the goal is to highlight the majority of Lumira’s amazing features and capabilities.

For this 1st part we will use a dataset that contains the following tax data:
Number of Taxpayers, Family Income and Total Tax for different Professional Groups in all Greek Subregions from 2006(FY) to 2011(FY).

a)Data Manipulation & Visualisation

1) Firstly, a Bar Chart displays the Number of Taxpayers belonging in each Professional Group by Year.

2) In order to visualise this information in a more understandable way, the Bar Chart is turned into a Line Chart.

3) The following Line Chart shows the Average per capita Tax for all the Professional Groups throughout the Years.

Average per capita Tax is a calculated measure that is calculated through the following formula :(Total Tax/# Taxpayers).

4) What comes to mind next, is exploring which Subregions are the ones that pay the most Taxes, aka have the higher Average per capita Tax.

For this reason, a Bar Chart in created and then sorted into descending order.

5) However, what if we would like to have this information for all the Regions and not only for the Subregions?

In SAP Lumira it takes only a few clicks to build a Geographical Hierarchy on Subregion. The embedded library is able to recognize names of Cities, Subregions, Regions and Countries all over the world, even when written in Greek.

So, changing the previous Bar Chart to display the Regions instead of the Subregions, we get the following visualization.

6) One of the most striking visualizations SAP Lumira includes, is the Choropleth Chart that enables the visualization of geographical information on a map.

In the following you can see the Avg per capita Tax for all the Greek Subregions.

7) And which Subregions are the wealthier, aka have a high Average per capita Income? Another Calculated Measure: (Family Income/# Taxpayers) was created and a Choropleth Chart once again can provide us with the answer.

8) What is more, selecting another impressive graph, which is called Geo Pie Chart, we are able to visualize the Average per Capita Tax by Region for all the different Professional Groups.


Having finished with the data manipulation and visualization, the next step is to create a Storyboard, composing some visualisations that can easily provide information about important observations.

The following Storyboard contains the first Bar Chart that was displaying the # Taxpayers by Professional Group and Year, as well as the two Choropleth Charts that were created before.

In the control panel, the Region and the Professional groups were added for further drill down on the graphs.

For example, when selecting “Central Macedonia” for Region and “Farmers-Breeders-Fishermen” for Professional group, the graphs are filtered and the outcome can be seen in the following image.

If you enjoyed this post, stay tuned for the second part of the Greek Tax Analysis.

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  1. Patrick Perrier

    One of the best Data Geek Challenge example.  Not just a series of charts and visualisation but some actual analysis and understanding can be done here!  Well done.

  2. Suseelan Hari

    Hi Anastasia,

    Thank you so much for your efforts and analysis.

    Keep up the good work. I understand how much pain to create this graphical representation.

    All the best! Waiting for new graphical representations, tables and charts.

    Once again thank you so much for sharing. 🙂


    Hari Suseelan


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