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This special technology guide from Dell Technologies and AMD will take a closer look at some of the biggest disruptors affecting energy companies, and also examine how big data analytics can help these firms reduce risk, drive down costs, and improve efficiency. 
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Use Google Flu Trends as an example of how things go wrong.
Phillip Trotter's insight:
Good article on risks of interpreting large scale data mining using google flu trends as an example. The conclusion that often data indications are a first point of a process that then requires scientific grunt work to identify if a given correlation is actually relevant or not and that reality is sometimes the grunt work wont be done because its hard, requires funding and takes time. Worth reading.
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Much of what we believe about Big Data is wrong, which will be demonstrated in 2014.
For many enterprises, Big Data remains a nebulous goal, rather than a current reality. Yet it's a goal that more and more enterprises are pushing to the top of their priority list. As Gartner surveys have shown, everyone is keen to board the Big Data bandwagon, yet a comparative few really understand why. And as Gartner analyst Svetlana Sicular points out, the myths that hold back Big Data adoption vary depending on where along the adoption curve an enterprise happens to be.In 2014, many of the sillier Big Data myths will crumble to be replaced by increased experience with data-driven applications... Via Jeff Domansky
Phillip Trotter's insight:
Over the years I have come to appreciate Garner's hypercycle - especially as technologies and terms become less fashionable. I am pretty certain 2014 will see a backlash to the term big data - just at the same time large scale data initiatives go into production in many enterprises and valuable deployment stories and application experience is shared.. Interesting article from readwriteweb.
Jeff Domansky's curator insight,
January 2, 2014 3:11 AM
What's the big deal about big data? Mostly, it's about the myths that prevent it from being better utilized.
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A proof-of-principle prototype for CancerLinQ™ was demonstrated at the 2013 ASCO Annual Meeting. This “learning health system” prototype was first unveiled on March 27 at an ASCO-hosted panel discussion on big data in cancer care at the National Press Club in Washington, DC. At the ASCO Annual Meeting, attendees were able to view a demonstration of the CancerLinQ prototype in the exhibit hall as well as attend an educational session on the product, which ASCO calls the first demonstration of the feasibility of a health information technology-based learning health system. - See more at: http://www.onclive.com/publications/oncology-business-news/2013/September-2013/CancerLinQ-Proof-of-Principle-Prototype#sthash.AoXUoYrD.dpuf
Phillip Trotter's insight:
Effective data analysis is going to be key in improving cancer treatment and the outcomes of the CancerLinQ project is a key first step in demonstrating potential solutions in this area.
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IBM Wants to Predict Heart Disease Through Big Data Analytics
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If you eat ice cream, you're more likely to drown. That's not true, of course. It's just that both ice cream and swimming happen in the summer. The...
Phillip Trotter's insight:
Interesting article on data analytics, pattern analysis and guessing. and some great comments on the article as well - Worth a read.
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The results of a study of 82 million tweets from 1,300 counties.
Phillip Trotter's insight:
Interesting article on measuring sentiment analysis through twitter data.
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Phillip Trotter's insight:
Arsttechnica article describing research published in Geology where researchers used publicly available data from 33 deep wells drilled by the oil and gas industry in the Gulf of Mexico combined with seismic images of the region to identify massive Seafloor 'landslides' which occured as the result of the Chicxulub impact. The asteroid impact which ended the reign of the dinasaurs shook loose sediment along well over 2,000 miles of submarine slopes along the east coast of the United States as well as the Gulf of Mexico. Link to the orginal Geology paper at the end of the article.
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Ready or not, enterprise IT is entering an insight-driven age of computing where big data analytics rules, says IBM.
Phillip Trotter's insight:
Like many industry players, IBM see a confluence of four factors -- social, mobile, analytics and cloud driving changes in computing and the need for machine learning being central to analytics. Information Week has an overview of IBM's strategy.
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All Things Digital GE CEO Jeff Immelt's Big Data Bet All Things Digital And that's where the industrial Internet comes in: Using big data analytics to track such changes and provide what Immelt describes as “guaranteed outcomes.” In the world of...
Phillip Trotter's insight:
Interesting insight from CEO of General Electric on where they see internet of things applying to their core businesses and what opportunities will arise from it.
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"Big data" is the jargon du jour, the tech world's one-size-fits-all (so long as it's triple XL) answer to solving the world's most intractable problems. The term is commonly used to describe the art and science of analyzing massive amounts of information to detect patterns, glean insights, and predict answers to complex questions. It might sound a bit dull, but from stopping terrorists to ending poverty to saving the planet, there's no problem too big for the evangelists of big data.
"The benefits to society will be myriad, as big data becomes part of the solution to pressing global problems like addressing climate change, eradicating disease, and fostering good governance and economic development," crow Viktor Mayer-Schönberger and Kenneth Cukier in modestly titled Big Data: A Revolution that Will Transform How We Live, Work, and Think.
So long as there are enough numbers to crunch -- whether it's data from your iPhone, grocery store purchases, online dating profile, or, say, the anonymized health records of an entire country -- the insights that can be gleaned from our computing ability to decode this raw data are innumerable.
Even Barack Obama's administration has jumped with both feet on the bandwagon, releasing on May 9 a "groundbreaking" trove of "previously inaccessible or unmanageable data" to entrepreneurs, researchers, and the public.
"One of the things we're doing to fuel more private-sector innovation and discovery is to make vast amounts of America's data open and easy to access for the first time in history. And talented entrepreneurs are doing some pretty amazing things with it," said President Obama.
But is big data really all it's cracked up to be? Can we trust that so many ones and zeros will illuminate the hidden world of human behavior? Foreign Policy invited Kate Crawford of the MIT Center for Civic Media to go behind the numbers:
Click headline to read more-- Via Chuck Sherwood, Former Senior Associate, TeleDimensions, Inc
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From
enigma
Search and discovery platform for big public data that exposes billions of public records across previously siloed datasets. (Looks interesting.
Phillip Trotter's insight:
The Enigma team recently won TechCrunch New York startup competition - check out the video of their presentation. Interesting product that pulls together a diverse data set with accessible query tools and api.
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RT @EmcienCorp: Our friends at @MailChimp are helping small businesses use #BigData. Find out how. http://t.co/Dk2mBBxFhn #bdw13 #bdw13ATL
Phillip Trotter's insight:
MailChimp are an interesting software company - who have helped a number of organisations analyze large scale data collections. Week of 22nd April sounds like they will be sharing a lot more. look forward to learning more on what they do and how they do it.
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Phillip Trotter's insight:
Good article on the differences between big data processing and HPC simulations. Worth reading to see where the two communities focus, worry about and can learn from one another.
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Phillip Trotter's insight:
Jorge Titinger, CEO of SGI has a good article on applications of HPC to Big Data including: Graphing and mapping: HPC-powered data mapping and graphing will lead to greater accuracy in business forecastingPattern visualizations: HPC-powered tools will emerge that can provide an intuitive view of complex data sets, enabling rapid identification of relationships for simple analysisScaling in-memory databases: HPC will allow enterprise in-memory systems to handle larger data workloads — allowing closer to complete data sets (over partial sets) to benefit from real-time analytics while in motionMeta-data: The importance of meta-data will jump dramatically — we’ll see enterprises realize leveraging meta-data analytics for virtualization and relational mapping can yield enhanced accuracy, new business insights and even reveal security threats
With the advent of on demand compute and cloud based processing it will be interesting to see how the HPC companies continue to differentiate from on demand suppliers such as amazon and microsoft. Jorge's 2014 outlook is interesting and more sane than many big data predictions - certainly worth reading.
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(Photo credit: Wikipedia) By Chris Meyer, Tim McGuire, Maher Masri, Abdul Wahab Shaikh Data is meaningless unless it helps make decisions that have measurable impact.
Phillip Trotter's insight:
Common sense summary article which boils down to: 1. Decide what you need to produce 2. Source raw data and know its provenance 3. Focus on quick processing, decisions and execution 4. Deliver insight and act 5. Build data / evidence driven decision making into organization culture.
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GDELT: Global Database of Events, Language, and Tone
Phillip Trotter's insight:
The Global Database of Events, Language, and Tone (GDELT) is an initiative to construct a catalog of human societal-scale behavior and beliefs across all countries of the world over the last two centuries down to the city level globally, to make all of this data freely available for open research, and to provide daily updates to create the first "realtime social sciences earth observatory." Nearly a quarter-billion georeferenced events capture global behavior in more than 300 categories covering 1979 to present with daily updates. Data is available for data scientists to mine and analyze - See more at: http://gdelt.utdallas.edu/#sthash.04oK6DrA.dpuf
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IBM uses Big Data to predict outbreaks of Dengue fever and Malaria
Phillip Trotter's insight:
IBM's one of a numer of companies pioneering advanced analytics for healthcare and health policy that will hopefully help inform and result in better decision and policy making stratergies in how we deal with infectious disease.
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by Joseph RIckert Nate Silver of 538 fame gave the President's invited address this year at the Joint Statistical Meeting in Montreal.
Phillip Trotter's insight:
Nat Silver's talk at the JSM focused on the links between journalism and statistics by presenting 11 principles for journalists that apply equally well to business and data analysts.
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‘Smart cities’ is a term that has gained traction in academia, business and government to describe cities that, on the one hand, are increasingly composed of and monitored by pervasive and ubiquitous computing and, on the other, whose economy and governance is being driven by innovation, creativity and entrepreneurship, enacted by smart people. This paper focuses on the former and how cities are being instrumented with digital devices and infrastructure that produce ‘big data’ which enable real-time analysis of city life, new modes of technocratic urban governance, and a re-imagining of cities. The paper details a number of projects that seek to produce a real-time analysis of the city and provides a critical reflection on the implications of big data and smart urbanism. Via Complexity Digest
luiy's curator insight,
July 28, 2013 8:16 AM
The term ‘smart city’ has been variously defined within the literature, but can broadly be divided into two distinct but related understandings as to what makes a city ‘smart’. On the one hand, the notion of a ‘smart city’ refers to the increasing extent to which urban places are composed of ‘everyware’ (Greenfield 2006); that is, pervasive and ubiquitous computing and digitally instrumented devices built into the very fabric of urban environments (e.g., fixed and wireless telecoms networks, digitally controlled utility services and transport infrastructure, sensor and camera networks, building management systems, and so on) that are used to monitor, manage and regulate city flows and processes, often in real-time, and mobile computing (e.g., smart phones) used by many urban citizens to engage with and navigate the city which themselves produce data about their users (such as location and activity). Connecting up, integrating and analysing the information produced by these various forms of everyware, it is argued, provides a more cohesive and smart understanding of the city that enhances efficiency and sustainability (Hancke et al., 2013, Townsend 2013) and provides rich seams of data that can used to better depict, model and predict urban processes and simulate the likely outcomes of future urban development (Schaffers et al., 2011; Batty et al., 2012). Everyware thus works to make a city knowable and controllable in new, more fine-grained, dynamic and interconnected ways that “improve[s] the performance and delivery of public services while supporting access and participation” (Allwinkle and Cruickshank 2011: 2). It also provides the supporting infrastructure for business activity and growth and stimulates new forms of entrepreneurship, especially with respect to the service and knowledge economy.
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Using nanostructured glass, scientists at the University of Southampton have, for the first time, experimentally demonstrated the recording and retrieval processes of five dimensional digital data by femtosecond laser writing.
Phillip Trotter's insight:
The new media storage allows unprecedented parameters including 360 TB/disc data capacity, thermal stability up to 1000°C and practically unlimited lifetime. It is going to be interesting to see this migrate from research to market as a data archiving platform.
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Big Data ROI Still Tough To Measure
Phillip Trotter's insight:
As initial projects get deployed I expect we will see more and more of these types of stories. All technologies do seem to follow Gartner's hype cycle and it given all the so called big data stories and deployments in 2012 - 2013 will be an interesting year.
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Toyota to roll out big data traffic service in Japan
Phillip Trotter's insight:
Interesting initiative being led by Toyota. Wonder if we will see other car manufacturers looking to offer similar services going forward...
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From
opengeo
Palantir's data platform, Gotham, enables data integration, search and discovery, knowledge management, secure collaboration, and algorithmic analysis across a wide variety of data sources.
Phillip Trotter's insight:
Palantir teamed with the OpenGeo to extend PostGIS to support WGS84 coordinate system and geodetic coordinates. This enabled Palantir to migrate from Oracle spatial to PostGIS as the underpinning spatial database for their Gotham platform. The benefits to the wider spatial community are signficiant since WGS84 based mapping is often a requirement in government and geoscience applications. Palantir's sponsored open source development undertaken by OpenGeo enables other to take advantage of the new features and integrate PostGIS into workflows. Click on the image or title to learn more.
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From
www
How the blistering pace of technological change could have a profound impact on healthcare.
Phillip Trotter's insight:
The combination of sensors and automated tests in areas of genetics and proteomics enable collection of largescale comprehensive health data for the first time. That data will generate insights into human biology, our bacterial biome and how our health systems work. Advances in large scale data processing, correlation and machine learning will help over the next decade to radically change our understanding of human biology. As data is collected and in silico experimentation mapped to invitrio understanding data will change our healthcare systems over the next 30 years. This BBC article gives a good insight into how and why this is starting to happen now.
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13 ways that big data analytics is helping energy companies manage the current level of disruption