Though the term business intelligence is sometimes a synionym for competitive intelligence, BI uses technology, processes, and applications to analyze mostly internal, structured data and business processes while competitive intelligence gathers, analyzes, and disseminates information with a topical focus on a company's competitors. If understook broadly, business intelligence can include the subset competitive intelligence.
Some economists are questioning whether Big Data will ever have the impact of the first Internet wave, let alone the industrial revolutions of past centuries. (News Analysis: Is Big Data an Economic Big Dud?
Ron Bodkin of Think Big Analytics discusses the best and worst practices for adopting big data technologies and actually getting results. Companies must beware of dangerous decisions, charlatans and disastrous missteps.
IBM-Studie Big Data ist nicht nur was für große Unternehmen Computerwoche Die IBM-Studie "Analytics: The real-world use of big data" zeigt, dass der Mittelstand weltweit das Thema Big Data in Angriff nimmt - etwa drei Viertel der befragten...
The impact of computing on the worldwide economy, and even on business, was subject to debate until it got personal around the turn of the ’80s. Same with networking before the Internet came along in the mid ’90s.
Big computing and worldwide communications — two capabilities that for decades were entirely the province of large organizations — exploded with boundless new value once they became personal. You and I can do far more with computing and communications today than companies and governments ever could with either when they ran those shows, and when both were just B2B businesses.
From the B2B perspective in 1980, personal computing was an oxymoron. If you wanted to do serious computing, you needed big machines on raised floors tended “data processing” professionals. There was no way individuals with desktop machines could do the same grade of work. That notion ended when human creativity was massively unleashed by tens of thousands of new apps that could do things for individuals — and organizations — that big machines and staffs never could.
Likewise, from the B2B perspective, personal networking in 1993 was also an oxymoron. Networks were things companies built, or used by the grace of giant telecom operators. Then the Internet came along, and subordinated those telecom operators (and cable operators as well) to the boundless new capacities of anybody with a computer and a connection to the vast new “cyber” spaces the Internet’s simple protocols opened.
What happened in both cases was individuals acquiring and exploiting capacities that were once exclusively corporate — and doing far more with those capacities than those corporations (and governments) ever could.
We forget that when we look at “Big Data” today. In Is Big Data an Economic Big Dud? for example, James Glanz of The New York Times writes, ”There is no disputing that a wide spectrum of businesses, from e-marketers to pharmaceutical companies, are now using huge amounts of data as part of their everyday business.” The whole piece is contained in the B2B frame: Big Data is something only big companies (and hot start-ups) have, care about, and put to use.
As power shifts from brands to consumers, knowing your consumer has never been more important. But brands are often clouded by big data.In the post-advertising world, many brands struggle to understand the people they’re selling to and why they behave as they do. As power shifts from brands to consumers, knowing your consumer has never been more important. Even the accounting firm PwC has woken up to the fact that “every industry participant will need to invest in customer understanding and engagement.”
But so long as this point is couched solely in data-analytics terms, it tells only part of the story.
It’s easy to feel lost and, oddly, reassured by the introduction of “big data” (defined by Gartner as volume, velocity and variety), or colossal swaths of demographic, behavioural and customer-preference numbers. History is littered with examples of how the misuse of big data can precipitate poor decision making on a massive scale. The U.S. military’s overreliance during the Vietnam War on quantified data at the expense of human observation in the field is a classic case (read Brian Bergstein’s piece in the MIT Technology Review [20 February, 2013] for background). In a different context, data-harvesting giant Tesco’s handling of the recent horse-meat crisis reveals that having a wealth of available data but little empathy for your audience and their world can obscure the bigger picture, thereby impeding effective decision making.
Recent studies indicate to behavioural economists that people don’t make decisions or act according to reason (read Daniel Kahneman’s Thinking, Fast and Slow  for a seminal exploration of the factors that do influence human decision making)....
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