New Roles for a New Year: Data Visualization Expert

Published : February 12, 2015

tablets-dislaying-data-visuallyWhen it comes to business compartmentalization, transparency has made something of a mess of things. A positive mess—one that encourages greater communication, better customer experiences and more efficient exchange of data— but a mess nonetheless.

For those who don't work in or study the facts and figures a business emits, a bucketful of percentages, growth rates or profit numbers can be confusing and even polarizing when taken out of context. Enter the data visualization expert: the new digital age's human answer to an ever-rising tide of data and blurred lines of communication. Used everywhere from logistics services to customer outreach, this job title carries a lot of weight and few boundaries.

An Undefined Necessity

The workplace is as diverse as ever— generations, cultural backgrounds, telecommuting and other differences are blended into an impressive force of commerce in today's business climate. While this diversity is excellent for any number of applications, it proves an interesting challenge when communicating an important data-based concept.

Trade news source SupplyChainBrainData goes as far to define data visualization as core to business intelligence, pointing out how closely the two need to work together for success. Experts in this emerging field work with information that may be proprietary to certain departments and extract the important data, re-structuring it to make it coherent to a larger audience. Because the need itself is still in its infancy— the internet itself, as we know it, is barely two decades old— data visualization has the unusual distinction of turning its own talents in on itself.

Effectively, this jack-of-all-trades title is tasked with helping struggling businesses visualize what data visualization can actually do for their own communication problems.

Visualizing New Solutions

The position— which may call for a single, specialized individual or a more traditional position applicant that counts it among their strengths— is often instructed not just to collect data, but to interpret it for a broad audience as well.

In Datawatch, writer Dan Potter recently discussed the natural products of data visualization trends, such as RFID tags that seamlessly report back to logistic services and real-time train and truck GPS coordinates. These systems, set in motion and monitored by data visualization experts, help to build a more accurate picture of where materials or products are, where they could be, and even the precise point of transportation delays. And companies are beginning to realize the beneficial effect of empowering these individuals to repair rifts with systems and tools of their own finding or design when a visualization expert finds a hole in his or her findings. 

What's Wrong With Pie Charts?

Clicking a button on a toolbar in a spreadsheet program may pull up generic bar charts or line graphs, but putting in enough nodes or images to properly convey a complex issue is nearly impossible. Data visualization experts go well beyond simply designing segmented shapes and listing numbers— they are intelligent and aware enough to compare and contrast with formats the audience already finds familiar. Simply put, complicated data requires complicated solutions, and turning data into images isn't a push-button process any longer— it's literally a job all on its own.

Tam Harbert of the website CIO noted that in mid-2013, it took only 6 months to see jobs requiring data visualization proficiency to leap 12%. Extrapolate that growth to 2015 and beyond and you have a new position in business and a solid employment trend behind it.

Omni-channel approaches and digital transparency are throwing more data at business leaders than ever before, and your business and service providers alike are clamoring for data presented in logical, user-friendly ways. The data visualization expert, new as they may be to business culture, is an invaluable resource in pushing back the tide of data confusion and connecting departments in meaningful ways.

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Topics: Supply Chain Workforce Management

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