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One of the most important aspects of big data is the ability to visualize the data in a way that it is understandable for (senior) management of an organisation. Visualizing data will help them understand the data and find new patterns and insights. There are some big data startups who are developing a completely new way of visualizing data. One of them is Ayasdi and another is Synerscope. They take a completely new approach to data, instead of the old-fashioned and not very insightful graphs and pie charts. If your organisation is able to gain valuable insights with interactive visuals, you can be one step ahead of your competition. A big data visualizer can help with creating these important insights.
A big data visualizer should be a creative thinker who understands User Interface design as well as other visualizations skills such as typography, interface design, user experience design and visual art design. This will give the big data visualizer the skills to turn abstract information from data analyses into appealing and understandable visualizations that clearly explain the results of the analyses.
However, the problem with a dedicated big data visualizer is that the big data scientist best understands the results of the data and therefore the story that is to tell. When turning over the results to the big data visualizer, misinterpretation and biased presentation of results can occur. A big data visualizer therefore needs to understand how big data analyses are done and he or she needs to have the necessary programming skills to actually build the visualizations. A background in computer science can help a big data visualizer better understand what is meant.
A big data visualizer should have a solid background in using source control, testing frameworks as well as agile development practices to create and build compelling data visualizations as well as lead and advice management on how the visualizations work. A big data visualizer should be able to tell a comprehensible story from the big data analyses; one that can be understood by the decision makers within an organisation.
Mapping data is a difficult process of transforming relational data into a graph. A big data visualizer should be able to use metadata, metrics as well as being able to use color, size and position to highlight, group and set-up a hierarchy in the graphics. A big data visualizer should be able to develop visualizations that attract the user to play with it and interact with the graph.
As a big data visualizer should be able to read the raw big data analyses, or even perform the analyses, as well as being able to design, illustrate and create the results there are several skills required:
- In-depth knowledge of JavaScript, HTML, and CSS as well as some statistical programming languages;
- Familiarity with modern (JavaScript) visualization frameworks, such as Gephi, Processing, R and/or d3js;
- Experience with common web libraries such as JQuery, LESS, Functional Javascript;
- Understanding of efficient and effective Human Computer Interaction;
- Sharp analytical abilities and proven design skills;
- A strong understanding of typography and how it can affect visualizations as well as layout, space and an inherent feel for motion;
- Proficient in Photoshop, Illustrator, Indesign as well as other Adobe Creative Suite products;
- Excellent written and verbal communication skills; be able to explain the work in plain language to management with no data experience.
In the end the most important job of a big data visualizer is to create compelling data visualizations that help decision makers in their work based on abstract data. Which exact skills are needed of course depends on the type of job that needs to be done. A big data visualizer however should always be able to select the best data visualization technique based on the characteristics of underlying data in order to illustrate certainty, patters or other statistical concepts that will guide decision-makers.
