Big Data Wisdom, Courtesy of Monty Python

Monty Python and the Holy Grail

One of the best 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…

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 Holy Grail Big Data 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.’ (1)

The correct response, of course, is to first understand essential details behind the question as King Arthur did. Jim Kaskade, CEO of tech consultancy Infochimps, recently suggested to InformationWeek a simple yet “practical and refreshing” question to ask:

Whether it’s churn, anti-money-laundering, risk analysis, lead-generation, marketing spend optimization, cross-sell, up-sell, or supply chain analysis, ask yourself, ‘How many more data elements can you add with big data that can make your analysis more statistically accurate?’

The answer to this key question will lead to additional important questions:

  • “What variety of data sources are needed to fulfill my business case – structured data, unstructured data and/or unstructured content?”
  • “How do I correlate structured and unstructured information together?”
  • “How do I integrate data and content so our users can analyze it on demand, using our existing data visualization tools?”

There is no one-size-fits-all “Holy Grail” Big Data technology out there. In reality, a successful Big Data architecture consists of multiple components to address the unique aspects of all your disparate data sources, structured and unstructured, internal and external. Keep that in mind and show the wisdom of a king by taking pause and asking a few basic business questions to stay on the right path to Big Data business success.

 

(1) Source: InformationWeek article by Doug Henschen, Vague Goals Seed Big Data Failures.

Back to the Future of Business Intelligence with H.P. Luhn

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.