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  Srovnání meziroční změny počtu obyvatel čtyř měst Moravskoslezského kraje. Výchozím bodem rok 2012 (100%), kdy se porovnává změna v jednotlivých letech vůči tomuto roku. Zdroj dat: ČSÚ

Process understanding and data modelling combination can make the best story we can create.  It seems that one of the most important things on the data analysis is to have exactly defined terms. Any data model could not be well explained if we have  doubts on terms,  we use in process flow and what is also defined as the data structure. If we use the same terminology in both parts: process flow and data model then it results in significant synergy efect. From that angle combination of the process and data understanding makes unique benefit that we understand  how things work and we can bery fast explain the data story on very detailed level knowing all the aspects. 

  The best thing is to start with drawing a diagram showing the process flow. I would recommend to draw two diagrams instead.   Big picture: One describing all the process details with focus on the main flow. That end2end visualisation can provide anytime the best overview and also focus on details if zoomed. That picture can be on several pages, no limitations. You can extract any part anytime if you need to check just that part. Only recomendation is to keep it updated.  2mins version: One page process visualisation with less elements but focus on the main flow. That picture should support you to describe the process in 2 minutes to an audience without any previous knowledge of that process. This version should be based on the Big picture and also kept updated. Storing the source files at one place secures preventing duplicity. You can create a pdf copy with a timestamp to identify what date is the diagram related to if you want to share it.  I would recommend to...

 Can process and data work together? Yes they can. Knowing of the process contributes to better understanding of the data structure. It works together.  Proces is linear in the most cases (Inputs and outputs) Data story is also linear (Beginning and the end) Put both to the same bottle can create unique story describing both and also showing what would potential process change do wit the data.