Recently, I got an opportunity to work in data visualization field. In the process, I started understanding more about the data visualization. I though, it would be great to place my learning in blog post, as it will help other going though this roller coaster. I am planning to put this in series of blog post, where I would explain data visualization, technologies available today, and how to achieve it.
List of other related articles
- Data Visualisation with D3
- What we did with D3
Picture is worth thousand words
Here is the popular saying “Picture is worth thousand words”. This phrase is the nutshell for Data visualization. When ones have cones of data and needs to analyze it, it is very easy get lost without any means to represent it. Here, where the data science comes into picture. Data visualization is about mapping values to visual. It about taking the structure information and figuring out the ways to translate into visual those are more readily understood.
Data visualization is display of quantitative information. How best to represent underlying data visually using colour, size and shape. It turning about turning number into pictures which one can remember, analyze and connect.
Patterns in Data
Data visualization was about the finding patterns is series of data. That is, sequences of measurements that follow non-random orders.
Let take an example, does this data series make sense?
Let plot them in the graphically in scatter dots
Now, you can see patterns and make sense out of the data more easily. That’s the work of data visualization.
Pattern in data help you to do Trend analysis. Trend allows you to predict what will happen in future, based on the historical data. It can be used in many contexts like risk management where tracking variances in cost and schedule helps you to mitigate risk. It helps to increase sales by studying consumer purchase behaviours, find fashion treads, social patterns, in financial sector, it helps in stock performance tracking, and list is endless.
Storytelling and dimension to the data
Everybody loves story. Stories are memorable, impactful and personal. Not many among us remember the statistical figures, but many remember a story. Data visualization allows us to make data more visual which in turn allow us to explore and understand the data in difference ways. Good data visualization are able to make “aah” moments, I got it, which are more impactful to the audience. It allows one to add the meaning to the data visualization.
Very successful stories follow an arc. A clear flow turns a collection of facts into a compelling narrative. It glues them together into a structure that makes sense. And the rising action of a story arc makes it more engaging and memorable. Tell stories with data means following
- Add context to the data which Audience would understand. It answer basic question, what’s the purpose of the data.
- Then, comes to the exploratory scene where audience tends to get the sense of data, what data is, what it can tell you. It is process to connect data in interesting ways, look data with different angle in unbiased and unleading way.
- Final is the explanatory phase, where one derive the meaning for the data. It concludes the objective to showcase the entire visualization.
Data Storytelling – Jock Mackinlay, PhD, Robert Kosara, PhD, Michelle Wallace
Tell a Meaningful Story With Data – Daniel Waisberg
Edward Tufte: Books – The Visual Display of Quantitative Information
Three steps to become a visualization/infographics designer – Alberto Cairo, Facebook