Note: This article was co-written by Mike Urbonas and Rik Tamm-Daniels.
One of our favorite parts of the hilarious 1975 King Arthur parody, Monty Python and the Holy Grail is the “Bridge of Death” scene: If a knight answered the bridge keeper’s three questions, he could safely cross the bridge; if not, he would be catapulted into… the Gorge of Eternal Peril!
Unfortunately, that’s exactly what happened to most of King Arthur’s knights…
The knights were either stumped by a surprise trivia question like, “What is the capital of Assyria?” – or responded too indecisively when asked, “What is your favorite color?”
Fortunately when King Arthur was asked, “What is the airspeed velocity of an unladen swallow?” he wisely sought further details: “What do you mean – an African or European swallow?” The stunned bridge keeper said, “Uh, I don’t know that… AAAGH!” Breaking his own rule, the bridge keeper was thrown over into the gorge, freeing King Arthur to continue his quest for the Holy Grail.
Many organizations are on “Big Data Holy Grail” quests of their own, looking to deliver game-changing analytics, only to find themselves in a “boil-the-ocean” Big Data project that “after 24 months of building… has no real value.” Unfortunately, many organizations have rushed into hasty Hadoop implementations, fueled by a need to ‘respond’ to Big Data and ‘not fall behind.’
Read the rest of this article on SmartData Collective.
My name is Sherlock Holmes. It is my business to know what other people do not know. — The Adventure of the Blue Carbuncle
Sherlock Holmes turned 125 years old last year, and he’s never been more alive and well. The world seems more captivated by Sir Arthur Conan Doyle’s legendary London detective than ever before. Much of this excitement has been driven recently by the smash BBC One TV series Sherlock, drawing rave reviews for its update of Holmes and Dr. Watson as present-day Londoners fighting 21st-century crime. (Similarly, the U.S. version of the series, Elementary, is also a major new hit.)
Pop culture critic and author John Powers cleverly explains Holmes’ enduring appeal as a literary hero and cultural icon:
Sherlock Holmes “possesses no superpowers — his parents weren’t wizards, no radioactive spider bit him — [and yet] his gifts are cool enough to be superhuman. Playing to our fantasies of being smarter than everyone else, Holmes performs jaw-dropping feats of perception.
It’s no coincidence that heightened interest in Sherlock Holmes coincides with the rapidly accelerating, proliferating sources of information around us: databases, documents/text, big data, social media, web content and more. Like Sherlock Holmes, we all want to make sense of seemingly unrelated information and “be smarter than everyone else” — or at least outsmart the competition, outsmart criminals and fraudsters, outsmart seemingly intractable business problems.
A quick review of Conan Doyle’s novels and short stories reveals Sherlock Holmes shared useful advice on effectively accessing, analyzing, and unifying information. His advice rings truer than ever in today’s increasingly information-rich but insight-deficient world.
When was the term “business intelligence” first coined? You might assume it was first conceived in the late 1980’s; coinciding with the initial emergence of companies offering visual analytic software, but the term was actually first used decades earlier by visionary IBM technology scientist Hans-Peter Luhn in his groundbreaking 1958 research paper, A Business Intelligence System.
Hans-Peter Luhn’s life work at IBM did not include quantifiable (structured) data. Rather, H.P. Luhn’s prolific IBM career focused on documents — letters, research reports, books — the unstructured content of his day.
Reading his paper today, it is clear that Luhn was well ahead of his time, envisioning critical technology components that set the stage for knowledge management and enterprise search today. And now, Luhn’s insights into the effective use of information, such as the vital need to answer three vital overarching questions – what is known, who needs to know, and who knows what – are more relevant to today’s business intelligence than ever before.
Read the entire blog article on the SmartData Collective.