smarterplanet: Beecham Research’s Sector Map shows segmentation of the M2M Market in semi-circular format, including 9 key Service Sectors, key Applications Groups within Sectors, and examples of Connected Devices within each Sector at the outer edge. Overall, Beecham Research tracks over 300 different device types. File is single page PowerPoint with high resolution image inserted. M2M = Machine-to-Machine.
joshbyard: Experiment Transmits Data from One Brain to Another James’ process of telepathic communication is rough, its results shaky, but the principle of brain-to-brain (B2B) communication is unquestionably met… In the experiment, the sender imagined a series of binary digits, broadcasting their choices by imagining movement in their right arm or their left. The resulting patterns of brain activity were recorded and expressed by an LED — one frequency to represent a one, another to represent a zero. The patterns are simply too arcane to be useful to the conscious mind, too quick and complex, but they’re not meant to be read like Morse code, in any case. When the LED signal travels to the recipient, it flashes into a very specific part of the eye (which part doesn’t matter much) and so the resulting optical signal is sent to a predictable section of the visual cortex. Surface electrodes just like those that originally recorded the signal are much better than people at making sense of the quick-flash LED language, seeing in the recipient’s brain more data than does the recipient themselves. Once the pattern has been reverse-engineered from LED back to arm-waving, the telepathic process is said to have concluded. (via Father-daughter duo have the world’s first brain-to-brain ‘telepathic’ conversation)
The Blue Collar Coder | Anil Dash →
Roundup of Big Data Forecasts and Market Estimates, 2012  urbanrelationsinfo: From the best-known companies in enterprise software to start-ups, everyone is jumping on the big data bandwagon. The potential of big data to bring insights and intelligence into enterprises is a strong motivator, where managers are constantly looking for the competitive edge to win in their chosen  markets.  With so much potential to provide enterprises with enhanced analytics, insights and intelligence, it is understandable why this area has such high expectations – and hype – associated with it. Given the potential big data has to reorder an enterprise and make it more competitive and profitable, it’s understandable why there are so many forecasts and market analyses being done today.  The following is a roundup of the latest big data forecasts and market estimates recently published: As of last month, Gartner had received 12,000 searches over the last twelve months for the term “big data” with the pace increasing. In Hype Cycle for Big Data, 2012, Gartner states that Column-Store DBMS, Cloud Computing, In-Memory Database Management Systems will be the three most transformational technologies in the next five years.  Gartner goes on to predict that Complex Event Processing, Content Analytics, Context-Enriched Services, Hybrid Cloud Computing, Information Capabilities Framework and Telematics round out the technologies the research firm considers transformational.  The Hype Cycle for Big Data is shown below: Predictive modeling is gaining momentum with property and casualty (P&C) companies who are using them to support claims analysis, CRM, risk management, pricing and actuarial workflows, quoting, and underwriting. Web-based quoting systems and pricing optimization strategies are benefiting from investments in predictive modeling as well.   The Priority Matrix for Big Data, 2012 is shown below:  Social content is the fastest growing category of new content in the enterprise and will eventually attain 20% market penetration.   Gartner defines social content as unstructured data created, edited and published on corporate blogs, communication and collaboration platforms, in addition to external platforms including Facebook, LinkedIn, Twitter, YouTube and a myriad of others. Gartner reports that 45% as sales management teams identify sales analytics as a priority to help them understand sales performance, market conditions and opportunities. Over 80% of Web Analytics solutions are delivered via Software-as-a-Service (SaaS).  Gartner goes on to estimate that over 90% of the total available market for Web Analytics are already using some form of tools and thatGoogle reported 10 million registrations for Google Analytics alone.  Google also reports 200,000 active users of their free Analytics application.  Gartner also states that the majority of the customers for these systems use two or more Web analytics applications, and less than 50% use the advanced functions including data warehousing, advanced reporting and higher-end customer segmentation features. In the report Market Trends: Big Data Opportunities in Vertical Industries, the following heat map by industry shows that from a volume of data perspective, Banking and Securities, Communications, Media and Services, Government, and Manufacturing and Natural Resources have the greatest potential opportunity for Big Data. Last week Gartner hosted Big Data Opportunities in Vertical Industries (August 7th) and provided an excellent overview of the research behind  Market Trends: Big Data Opportunities in Vertical Industries.  The following graphic was included in the webinar showing big data investments by industry.  The Wikibon Blog has created an excellent compilation of big data statistics and market forecasts.  Their post,  A Comprehensive list of Big Data Statistics, can be found here.  They’ve also created an infographic titled Taming Big Data.   You can find The Big List of Big Data Infographics here. The Hadoop-MapReduce market is forecast to grow at a compound annual growth rate (CAGR) 58% reaching $2.2 billion in 2018. Source:Hadoop-MapReduce Market Forecast 2013-2018 Big data: The next frontier for innovation, competition, and productivity is available for download from the McKinsey Global Institute for free.  This 156 page document authored by McKinsey researchers is excellent.  While it was published last year (June, 2011), if you’re following big data, download a copy as much of the research is still relevant.  McKinsey includes extensive analysis of how big data can deliver value in a manufacturing value chains for example, which is shown below: (via urbanrelationsinfo)

Roundup of Big Data Forecasts and Market Estimates, 2012 

urbanrelationsinfo:

From the best-known companies in enterprise software to start-ups, everyone is jumping on the big data bandwagon.

The potential of big data to bring insights and intelligence into enterprises is a strong motivator, where managers are constantly looking for the competitive edge to win in their chosen  markets.  With so much potential to provide enterprises with enhanced analytics, insights and intelligence, it is understandable why this area has such high expectations – and hype – associated with it.

Given the potential big data has to reorder an enterprise and make it more competitive and profitable, it’s understandable why there are so many forecasts and market analyses being done today.  The following is a roundup of the latest big data forecasts and market estimates recently published:

  • As of last month, Gartner had received 12,000 searches over the last twelve months for the term “big data” with the pace increasing.
  • In Hype Cycle for Big Data, 2012, Gartner states that Column-Store DBMS, Cloud Computing, In-Memory Database Management Systems will be the three most transformational technologies in the next five years.  Gartner goes on to predict that Complex Event Processing, Content Analytics, Context-Enriched Services, Hybrid Cloud Computing, Information Capabilities Framework and Telematics round out the technologies the research firm considers transformational.  The Hype Cycle for Big Data is shown below:

  • Predictive modeling is gaining momentum with property and casualty (P&C) companies who are using them to support claims analysis, CRM, risk management, pricing and actuarial workflows, quoting, and underwriting. Web-based quoting systems and pricing optimization strategies are benefiting from investments in predictive modeling as well.   The Priority Matrix for Big Data, 2012 is shown below:

  •  Social content is the fastest growing category of new content in the enterprise and will eventually attain 20% market penetration.   Gartner defines social content as unstructured data created, edited and published on corporate blogs, communication and collaboration platforms, in addition to external platforms including Facebook, LinkedIn, Twitter, YouTube and a myriad of others.
  • Gartner reports that 45% as sales management teams identify sales analytics as a priority to help them understand sales performance, market conditions and opportunities.
  • Over 80% of Web Analytics solutions are delivered via Software-as-a-Service (SaaS).  Gartner goes on to estimate that over 90% of the total available market for Web Analytics are already using some form of tools and thatGoogle reported 10 million registrations for Google Analytics alone.  Google also reports 200,000 active users of their free Analytics application.  Gartner also states that the majority of the customers for these systems use two or more Web analytics applications, and less than 50% use the advanced functions including data warehousing, advanced reporting and higher-end customer segmentation features.
  • In the report Market Trends: Big Data Opportunities in Vertical Industries, the following heat map by industry shows that from a volume of data perspective, Banking and Securities, Communications, Media and Services, Government, and Manufacturing and Natural Resources have the greatest potential opportunity for Big Data.

  • Big data: The next frontier for innovation, competition, and productivity is available for download from the McKinsey Global Institute for free.  This 156 page document authored by McKinsey researchers is excellent.  While it was published last year (June, 2011), if you’re following big data, download a copy as much of the research is still relevant.  McKinsey includes extensive analysis of how big data can deliver value in a manufacturing value chains for example, which is shown below:

(via urbanrelationsinfo)

It's Time to Rethink Continuous Improvement - Ron Ashkenas - Harvard Business Review →
joshbyard: Is Success in Miniaturization its Own Worst Enemy? Nowadays two transistors, fabricated a few dozen nanometers apart on the same piece of silicon, will not have the same electrical properties. It’s one of the key barriers that the global chip industry—with sales of US $300 billion—must overcome to keep producing better, faster, cheaper, more energy-efficient chips. The culprit is scaling. Chips have improved because their transistors and connecting wires have kept getting smaller, but now they’re so small that random differences in the placement of an atom can have a big impact on electrical properties. Some batches vary so much that more than half will run 30 percent slower than intended or consume 10 times as much power as they should when on standby. Some of these defective chips can be sold at a discount, but if they’re for application-specific designs—say, for mobile phone communication or video encoding—they might find no better destination than the junkyard. And the defect rate will only get worse as transistors continue to shrink. (via The Threat of Semiconductor Variability - IEEE Spectrum)
IT hiring forecast optimistic ... for now →
CEOs and CIOs Are Increasingly Disconnected →