Data Visualization is a form of visual communication. Basically, information has been  abstracted in some form including attributes or variables for the units of information. 

[ngg_images source=”galleries” container_ids=”7,9″ display_type=”photocrati-nextgen_basic_imagebrowser” ajax_pagination=”0″ order_by=”sortorder” order_direction=”ASC” returns=”included” maximum_entity_count=”500″]

Data Visualization is an interesting field which provides an aesthetic dimension to all types of data. My learning objectives from this course include learning frameworks and tools like D3.js, Tableau and using Python to create statistical visualization which will help to derive unexplored patterns and insights in the data. Also, I want to explore the area of Business Intelligence by using tools like Tableau and Qlikview. 

My journey with Data Visualization commenced with an interesting exercise in class where we had to form groups and think about some real life data visualization topic and present a physical data visualization by using the available props in the class.  My group decided to  visualize the data of food preferences of students present in the class. We collected the data regarding the geographic location of each person, their most favorite cuisine and least favorite cuisine. The data was recorded and we created an index which marked every cuisine with a corresponding colored pin. The physical visualization comprised of a world map and colored pins placed on countries which denoted the type of cuisine preferred. 

The salient patterns observed through this visualization were the following:

  • People of North America preferred Japanese cuisine
  • People from India preferred traditional Indian cuisine.

The data collected did not represent any statistical distribution and it was characterized by some outliers. The challenging task in this activity was data collection and aggregating it to generate the menu index. The future scope of our task was to categorize the cuisine distribution across the world into categories like vegetarian, gluten free and non-vegetarian . But this objective was not possible to be accomplished considering the time constraints and other limitations.