"The Visual Organization" author Phil Simon discusses data visualization tools and their power to change business conversations.
Big data can be big chaos. But finding clarity -- and business opportunities -- in that chaos has never been more important.
Presenting data clearly and visually is now as important as finding it. Enter data visualization tools that create heat maps, data relationship trees, and geospatial overlays. They provide visual ways to explain a sales trend to the CEO in a few minutes. They turn data into a conversation.
This is the timely subject of Too Big To Ignore author Phil Simon's upcoming book, The Visual Organization: Data Visualization, Big Data, and the Quest for Better Decisions (Wiley, 2014), due out next month.
Simon sat down with InformationWeek to discuss how to become more of a "visual organization," the perils of being a big data laggard, and more.
IW: Phil, you emphasize in your book, The Visual Organization, that data visualization is more than just pie charts and pretty pictures that display data sets. What are key features and functions of contemporary dataviz tools that help organizations make better decisions?
PS: First, the best-of-breed dataviz tools these days are sophisticated. They can handle an array of data sources. They can easily accommodate not only internal enterprise data sources like relational databases, but external sources such as Twitter firehoses, third-party scripts, open datasets, charting libraries, and the like.
Second, they're not restricted to structured data linked via traditional drivers and ETL [extract, transform, load]. Many can handle semi-structured and even unstructured data sources from APIs. Third, they are interactive; that is, they do not merely present static data, they encouragedata discovery and exploration.
An interactive dataviz tool used by Netflix employees to view how content is consumed by date, hour, and category.
Source: Netflix Technology Blog
Fourth, they are much more user-friendly than the applications of years past. While technical sophistication is beneficial, you don't have to be a programmer or data scientist to make sense of data in Spotfire or Tableau, for instance. Finally, they lend themselves to sharing, both internally and for the outside world.
IW: What's preventing companies from becoming visual organizations? Dataviz tools are not difficult to implement, and popular companies like Netflix and LinkedIn prove they work.
PS: To be fair, most organizations already employ data visualization tools. Microsoft Excel is the classic example. Now, I love Excel and it has evolved over the last two decades. For instance, PowerQuery is pretty neat. But it's a mistake to believe that Excel can effectively handle all of an organization's data visualization needs.
Many large organizations implemented expensive business intelligence software in the 1990s and 2000s. Those BI tools, though, are predicated on dashboards, traditional analytics, KPIs, etc. They assume to a large extent that a user knows what he or she is looking for.
To answer your question though, old habits die hard. There's an "ain't broke, don't fix it" mindset in many organizations. Many employees fear the unknown and stick with tried-and-true tools like Excel. Plenty of CXOs insist upon firm ROI calculations before making any new major technology purchase. And let's not forget that organizations have had for the most part dismal batting averages implementing new systems, which was the subject of one of my previous books, Why New Systems Fail.
IW: What types of businesses are becoming visual organizations? Which ones are resisting?
PS: Organizations that understand the potential power of data (big and small) are jumping on board first. Companies like Cisco, Pandora, ESPN, Twitter, LinkedIn, Facebook, eBay, and others are discovering fascinating things
Shane O'Neill is Managing Editor for InformationWeek. Prior to joining InformationWeek, he served in various roles at CIO.com, most notably as assistant managing editor and senior writer covering Microsoft. He has also been an editor and writer at eWeek and TechTarget. ... View Full Bio
6 Tools to Protect Big DataMost IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.
Big Data Brings Big Security ProblemsWhy should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.
Top IT Trends to Watch in Financial ServicesIT pros at banks, investment houses, insurance companies, and other financial services organizations are focused on a range of issues, from peer-to-peer lending to cybersecurity to performance, agility, and compliance. It all matters.
Join us for a roundup of the top stories on InformationWeek.com for the week of October 9, 2016. We'll be talking with the InformationWeek.com editors and correspondents who brought you the top stories of the week to get the "story behind the story."