What looks like a doom, is a boom

Ronald Gruia, from Frost and Sullivan, pointed out via a tweet  the May 6, 2014  article from Venture Beat  How startups are dying faster than they’re being created, in 2 charts

The second figure is a histogram
The data comes from the prestigious Brookings Institute Quoting from the article
A disturbing new report from the Brookings Institute finds that startup growth, a primary engine of America’s economic power, is slowing down.
“Recent evidence points to a U.S. economy that has steadily become less dynamic over time,” the authors concluded. In fact, the number of new businesses has steadily been cut in half since 1978.
In an email to VentureBeat, a spokesperson for Brookings said the research “does apply across all sectors, including tech.”
This is big trap of Big Data.Letting machines crunching numbers and not doing a proper fact finding to put the number outcomes in right perspective.

In another entry on this blog:  From Big Data to Big Decisions , I say:
    I quoted the opinion of Larry Fink,  the CEO and Chairman of the largest asset management firm in the word, Blackrock (three and half trillions dollars under their administration)
  • The markets in America reflect a lot of fear. We are bombarded with information that we can not make sense out of it. We can't decide whether this  Big Data information  is good or is bad.
  • As a result every CEO, government decision maker handling money only invests short term.  Some CEO's buy back shares to invest the cash in government bonds at 2% interest rate. Companies sit on lots of cash, too afraid to spend it. 
  • Banks have tons of money, they sit in the vaults without making loans. The banks want to make loans, but say someone who qualified for a loan in 2007, does no longer qualify. The companies who qualify, they do not need any loans as they have tons of cash already.
The main inhibitor, it is worth repeating, is not Big Data itself. It is the fear of it. The top decision makers in our society, the CEOs and the Government economists, are unsure how this big data can be used.
In light of Mr. Fink observations, -  (which means when Blackrock sneezes, we must all take out our kleenex-es, ready to use), - once the fear of of Big Data is overcome, we must expect an EXPLOSION of start ups and investments. This provided we do not make another bubu by imposing sanctions to Russia and / or other destabilizing politically motivated move.

This is the true meaning of Brookings Institute graphs, in my humble opinion.

Big data is the same data we always knew. It is now very big. There is no such thing as small data. The biggest danger is to be enraptured by the fancy-mancy machine learning to forget the facts

Here is a quote from another blog entry Why Big Data is not for everyone
Bradley Voytech shows his calculations on how many people were born in British Empire  between September 4, 1752 and September 13, 1752. He extracted world's data births for that period, extrapolated and then applied a % proportional to the British Empire share of the then known world population
However it was impossible for any citizen of the British Empire to be born between September 4, 1752 and September 13, 1752. 
Year 1752 (MDCCLII) was a leap year starting on Saturday of the Gregorian calendar, and a leap year starting on Wednesday of the 11-day slower Julian calendar. In the British Empire, it was the only year with 355 days, as September 3 through September 13 were skipped.
 Sometimes the great algorithms we have can fail, if we have no knowledge of the real world
Define speed as "How quickly we can go from data to decisions?", said one young founder of a big data company. But this speed is only partially dependent upon technology.
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