Monday, January 30, 2012

Internet 2011 in numbers


Posted in Main on January 17th, 2012 by Pingdom

So what happened with the Internet in 2011? How many email accounts were there in the world in 2011? How many websites? How much did the most expensive domain name cost? How many photos were hosted on Facebook? How many videos were viewed to YouTube?
We’ve got answers to these questions and many more. A veritable smorgasbord of numbers, statistics and data lies in front of you. Using a variety of sources we’ve compiled what we think are some of the more interesting numbers that describe the Internet in 2011.


  • 3.146 billion – Number of email accounts  worldwide.
  • 27.6% – Microsoft Outlook was the most popular email client .
  • 19% – Percentage of spam  emails delivered to corporate email inboxes despite spam filters.
  • 112 – Number of emails sent and received  per day by the average corporate user.
  • 71% – Percentage of worldwide email traffic that was spam (November 2011).
  • 360 million – Total number of Hotmail users  (largest email service in the world).
  • $44.25 – The estimated  return on $1 invested in email marketing in 2011.
  • 40 – Years since the first email was sent , in 1971.
  • 0.39% – Percentage of email that was malicious  (November 2011).


  • 555 million – Number of websites  (December 2011).
  • 300 million – Added websites in 2011.

Web servers

  • 239.1% – Growth in the number of Apache websites  in 2011.
  • 68.7% – Growth in the number of IIS websites  in 2011.
  • 34.4% – Growth in the number of NGINX websites  in 2011.
  • 80.9% – Growth in the number of Google websites  in 2011.

Friday, January 6, 2012

Search for public data in Google Web Search

Search for public data in Google Web Search

Watch a video about the feature:

A subset of datasets from the Public Data Explorer are indexed in Google Web Search. Searching for metrics from these datasets will generate a graph at the top of your search results, and clicking on this graph will take you to the corresponding visualization in the Public Data Explorer.
More information about each of the searchable datasets and their associated triggering queries is shown in the table below:
Dataset (Provider)Data DetailsExample Queries
World Development Indicators
(World Bank)
A variety of metrics related to world growth and development, by year, by country.
See the complete list of metrics.
GDP of France ]
Population of China]
Energy consumption Iceland ]
Unemployment in the US
(US Bureau of Labor Statistics)
Unemployment rate by month, by state, county, and for the country as a whole.US unemployment ]
Unemployment in Wisconsin ]
Population in the US
(US Census Bureau)
Population by year, by state, county and for the country as a whole.Population of Texas]
Population Nassau County New York ]
Unemployment in Europe
Unemployment by month, by country.Unemployment in France ]
Minimum Wage in Europe
Minimum wage in Euros by half-year, by country.Portugal minimum wage ]
Government Debt in Europe
Government debt as percentage of GDP by year, by country.Germany government debt ]
Broadband Penetration in Europe
Broadband connections per hundred inhabitants, by half-year, by country.Broadband penetration Sweden ]
Stay tuned for more datasets in Google search in the future!
updated 12/19/2011

Wednesday, January 4, 2012

From SearchBusinessAnalytics: Skills shortage, training present pitfalls for 'big data' analytics

Beth Stackpole, Contributor

Published: 1 Jan 2012
The biggest challenges related to “big data” analytics, according to consultants and IT managers, boil down to a simple one-two punch: The technology is still fairly raw and user-unfriendly, and there aren’t enough skilled experts to go around.
A lot of big data technologies -- like Hadoop and MapReduce -- hail from the open source world, developed by Internet pioneers such as Google and Yahoo to take on the problem of cost-effectively processing large volumes of information, including both structured andunstructured data. As a result of this orientation, most of the technologies lack the maturity and accessibility of traditional databases and data management suites, and there is still a limited selection of complementary analytics tools available to make these environments feel familiar to many data warehousing and analytics professionals.