“The ability to simplify means to eliminate the unnecessary so that the necessary may speak” Hans Hoffman
These days it seems you can’t start a post about any trend in the big data world without quoting some truly astronomical numbers. Just so we don’t offend anyone take a look at these – every single day the world creates 2.5 Quintillion bytes of data and over 90% of all the data in the world today is likely to have been created in the last 2 years. Where there is data there is likely to be an enterprise looking to leverage it for competitive advantage – one reason why big data initiatives abound all around. The market for global big data is slated to touch $ 38 Billion this year – how’s that for an astronomical number.
That being said – the value really is not in the data but in how it can be used to increase sales and marketing, improve operational efficiency, engage employees better and make the enterprise nimbler and more responsive. This implies an agility in decision making that, almost by definition, would have to be at the edges of the organization and decentralized rather than at the center of a complex organizational structure.
- The challenge is how to equip the managers at the frontlines, who should be taking these decisions, with the information they need to take those decisions?
- Time is a factor too. Wouldn’t the insights have to reach the edge locations quick enough to allow timely action?
- Given varying capabilities and skill sets in that audience, how to distil the insights from the mountains of data and how to present it to them in an easy-to-understand manner?
- How to give them the capability to apply their own filters to the data to draw out similarly easy-to-understand insights that are most relevant to them?
- Is it possible to be proactive and embed this actionable insight right into their daily workflow so that it becomes a part of the process, rather than something up to the discretion of the line manager?
The Tableau and Qlikview practitioners out there probably know where we’re going with this now – yes, we are, not so subtly, building the case for Data Visualization.
A simple definition of Data Visualization in WhatIs goes, “Visualization is the process of representing abstract business or scientific data as images that can aid in understanding the meaning of the data.” This has, of course, gone far beyond yesterday’s dashboards and graphical reports. Given the volume, velocity, and variety of data that enterprises have to deal with – bringing Analytics to bear on it to find the gems hidden therein is no easy task. Enterprises are turning to Data Visualization to look at the data differently and then to present it differently making this a key element of the big data initiative of the enterprise. Enterprises are mobilizing vast quantities of resources, cash, time and effort, behind their big data initiatives and can use all the help they can get to make them more effective.
The “Visualization” option seems to be working – Aberdeen reported recently, “Organizations with real-time visualization are able to obtain critical information within the decision window 78% of the time, or 22% more often than organizations without real-time visualization.” That’s pretty comprehensive and enterprises are paying attention as is apparent from the $ 4.12 Billion market size for Data Visualization in 2015. Expect more converts, as the same report from Mordor Intelligence expects the corresponding number for 2020 to be just shy of $ 7 Billion.
Renowned information architect David McCandless is reported to have said, “By visualizing information, we turn it into a landscape that we can explore with our eyes, a sort of information map. And when you’re lost in information, an information map is kind of useful.” That sets up the potential value of data visualization for an enterprise as well as any definition could – so the next time your enterprise seems to be drowning in data remember to take a deep breath and visualize!
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