Les Paul’s Electric Guitar & Unified Information Access: Two Platforms of Innovation

Les Paul. Source: Rock & Roll Hall of Fame

Without Les Paul (1915-2009), it’s safe to say that rock and roll as we know it would not exist. Inducted into the Rock and Roll Hall of Fame in 1988, Les Paul was a virtuoso guitarist and pioneer in the development of the solid-body electric guitar. His innovations helped make the unforgettable sound of rock and roll possible.

There are some interesting analogies between Les Paul’s modern electric guitar, which ushered in a new era of modern music, and unified information access, modern technology that leverages advanced enterprise search for deeper analytic insights that go well beyond what traditional tools can offer.

Early in his musical career, Les Paul found his acoustic guitar was drowned out by the other instruments in a band. The acoustic guitar was simply too quiet. In its own way, text-based unstructured information (documents, wikis, email, social media) has also been too “quiet.” Quickly drowned out by more easily accessible structured databases, unstructured content was largely ignored by data analysts for decades.

Early efforts to use a microphone or an amplifier with a hollow-body acoustic guitar in Les Paul’s day resulted in poor sound quality and feedback. Similarly, unstructured content also defied initial efforts to integrate it with other information sources, such as trying to store it within relational databases. Unfortunately, most database methods do not perform full-text searching of content, and those that do require the content to be stored and organized in database tables. Effective textual searching requires linguistics and text analytics is commonly found not in relational databases, but in enterprise search technologies.

The methods for accessing unstructured content and structured data remained divided for decades: enterprise search engines being used for finding unstructured content and relational database systems for retrieving structured data.

Applying his musical talent and inventor’s mind, Les Paul built one of the very first solid-body electric guitars, culminating in 1952 with the classic Gibson Les Paul guitar. Thanks in large part to Les Paul, the guitar was definitely no longer the quietest instrument in the ensemble!

Les Paul with his Gibson Les Paul solid body electric guitar and 8-track tape recorder. Source: les-paul.com

Between his electric guitar and breakthroughs in multi-track sound recording, Les Paul created a platform of innovation that enabled entirely new types of musical expression that were previously impossible. Indeed, the Rock and Roll Hall of Fame rightly honored Les Paul as an architect of rock music.

Similarly in the business world, we have seen unified information access – a new technology platform of innovation – enable new ways to inform, educate and entertain people, through a single interface, portal, website or device, replacing what used to be dozens of individual products or standalone software packages.

UIA is helping transform businesses by freely integrating, joining and presenting all related enterprise information – structured and unstructured, internal and external alike – and building amazing new business applications no one has ever seen before.

Using Business Intelligence for Effective Business Storytelling

An appropriately told story has the power to do what rigorous analysis couldn’t: to communicate a strange new idea and move people to enthusiastic action.

~  Steve Denning, “The Leader’s Guide to Storytelling”

Business storytelling, campfire optional

“…And my phone log analysis proved the calls were coming from INSIDE THE HOUSE!!”

The most successful business intelligence professionals are also great storytellers. Regardless of your BI tools of choice, it’s important to note that “business storytelling” is not synonymous with infographics or data visualization. Every analytic tool can slice and dice data in a multitude of ways, but, of course, correlation is not causation. (More on this in a moment…)

Also, effective business storytelling does not necessarily require advanced data visualization tools. Any organization can take a the first step towards better storytelling by following universal best practices when creating even the most simple chart. Data consultant and author Thomas Redman recently wrote: “As Edward Tufte advises, label the axes, don’t distort the data, and keep chart-junk to a minimum.”

Redman’s next recommendation is also very simple: annotate your charts. “While annotations do not replace a well-told story, they do give the reader some inkling of what’s involved.”

Take a look at the “before” and “after” charts cited by Redman in his article. The annotations in the “after” chart tell a story how the company successfully improved customer data quality were successful, all in a very simple line chart:

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The chart annotations (above) are not just helpful notes; they also comprise a second set of data (the key milestones of the company’s data quality program – by month), correlated with the monthly data quality measures. As a result of this data correlation, a time series cause-and-effect story emerges, complete with a beginning, middle, and a happy ending.

This leads to a key point: the most compelling business stories present strong correlation-causation relationships using many disparate yet complimentary sets of data.

Perhaps you have seen Charles Joseph Minard’s 1869 data visualization of Napoleon’s army in the Russian campaign of 1812. It was deservingly praised by Edward Tufte in his classic book The Visual Display of Quantitative Information: “It may well be the best statistical graphic ever drawn.”

Charles Josepn Minard's Chart of Napoleon's 1812 March to Russia (1861).

Source: Scimaps.org. Click map to view/enlarge image. See also: http://www.edwardtufte.com/tufte/posters

Minard painstakingly correlated multiple data sources: the movements of Napoleon’s army over time, their geographical location – marching to Moscow and then retreating from it – with the (rapidly narrowing) thickness of the line representing the number of Napoleon’s men, falling in battle as well as from deadly subzero temperatures that hit a low of -30⁰ F/-38⁰ C.

Minard then brought his many datasets together to very effectively tell the story of Napoleon’s futile Russian campaign and the misery of his soldiers, resulting in massive casualties that wiped out the Grande Armee.

Fast forward to today: Big data infrastructures and analytics hold huge potential to not only tell the story of the loss of life from violent conflicts of past history, but also in the future – by piecing together stories that help prevent global violence before it actually happens.

This critical world goal was covered in a Foreign Policy magazine article, Can Big Data Stop Wars Before They Happen? Author Sheldon Himelfarb cites three key trends justifying optimism that the answer will soon become a clear “Yes”.

First, Himelfarb points out the increasing amounts of data being generated by more and more people through digital devices; and second, our expanded capacity to collect and crunch data like never before. But the third trend he notes is the most critical to developing a clear story of human sentiment that can forewarn us of future violence:

When it comes to conflict prevention and peace-building, progress is not simply a question of “more” data, but also different data. For the first time, digital media – user-generated content and online social networks in particular – tell us not just what is going on, but also what people think about the things that are going on.

Excitement in the peace-building field centers on the possibility that we can tap into data sets to understand, and preempt, the human sentiment that underlies violent conflict.

Thankfully, the stories we want and need to tell in our respective organizations don’t fall into this same literal life-or-death category. However, all effective business storytelling requires the same two core elements:

  • Not just “more” data… Different data. Integrate of as many varieties of complimentary data as possible on the backend – structured and unstructured, internal and external. Doing so lets you present what has happened with strong correlation/causation, as well as enabling deeper advanced analytics (e.g., location-based, sentiment, predictive).
  • Clear, annotated, “junk-free” data visualizations. Combine and present your data on the front end as a compelling story that conveys understanding, empathy and a sense of urgency to take action.