BRIT Receives Upgrade
January 13, 2012
Actuate Corporation, the creator of BRIT, is already a proven leader when it comes to open source business intelligence (BI) platforms but they have garnered even more attention with the launch of BRIT Performance Analytics according to the SourceWire article “Actuate Launces BRIT Performance Analytics.” The new platform “BIRT Performance Analytics enables organizations to implement closed loop performance management by incorporating capabilities that help discover problem areas, analyses root causes and drive improvements. “ Brit Performance Analytics brings a few notable benefits including initiative management, live excel spreadsheets and improved Performance Dashboards. One of the most important additions is mobility. Users will be able to get performance information on their mobile device which is extremely important in such a mobile based world. Chief Executive and Director of Research at The Advanced Performance Institute, Bernard Marr comments” Actuate truly understands the challenges faced by organizations today and what’s needed to help them succeed in a highly competitive, complex global marketplace.” With the overwhelming success and support of the new BRIT platform it seems Actuate managed to make a good thing even better.
April Holmes, January 13, 2012
Sponsored by Pandia.com
Please, Do Not Feed the Oracle
January 12, 2012
SAND Technology provides Enterprise Analytic Database Platforms. SAND Analytic Platform is a column based management system that focuses on optimizing data sharing throughout entire Enterprises. Mike Pilcher Chief Operating Office of SAND Technology provides an amusing view of Oracle in the SAND.com article “Just One More Water-Thin Mint, Mr.Ellison?.” He uses a Monty Phyton film to describe Oracle’s morbidly obese product line and the result of adding Endeca to the mix. “you will remember Mr. Creosote eating just one more wafer-thin mint too many… before exploding into a million messy pieces. Is the acquisition of Endeca Oracle’s one wafer-thin mint too many?” Oracle is not designed for Big Data analytics and Endeca just adds to the confusion. Pilcher feels “Extracting and augmenting structure onto unstructured data and merging it with structured data is the future of Big Data analytics, “ and praises Oracle for realizing this but points out the importance of having “a database designed and built to handle it, not a monster overfed on an endless supply of wafer-thin acquisitions.” Looks like Pilcher is really saying “Please don’t feed the Oracle.”
April Holmes, January 12, 2012
Sponsored by Pandia.com
Prediction Data Joins the Fight
January 12, 2012
It seems that prediction data could be joining the fight against terrorism. According to the Social Graph Paper article “Prediction Data As An API in 2012” some companies are working on developing prediction models that can be applied to terror prevention. The article mentions the company Palantir “they emphasize development of prediction models as applied to terror prevention, and consumed by non-technical field analysts.” Recorded Future is another company but they rely on “creating a ‘temporal index’, a big data/ semantic analysis problem, as a basis to predict future events.” Other companies that have been dabbling in big data/prediction modeling are Sense Networks, Digital Reasoning, BlueKai and Primal. The author theorizes that “There will be data-domain experts spanning the ability to make sense of unstructured data, aggregate from multiple sources, run prediction models on it, and make it available to various “application” providers.” Using data to predict the future seems a little farfetched but the technology is still new and not totally understood. Everyone does need to join the fight against terrorism but exactly how data prediction fits in remains to be seen.
April Holmes, January 12, 2012
Sponsored by Pandia.com
Big Data in 2012: Reliable Open-Source Software Required
January 11, 2012
Enthusiasm and optimism that Big Data as a concept is the next big thing. We are almost ready to board the Big Data bull dozer. The hoopla surrounding Big Data has not died down in 2012. Instead, the concept demonstrates the continuing environment of processing and analysis.
As businesses become aware that the Big Data trend is here to stay, publishers are looking for reliable support. The Apache Hadoop project develops open-source software for reliable, scalable, distributed computing. The company offers much in the way of dealing with unstructured data and is setting the pace for consolidation as well as personalization. I came across an interesting article, “State of the World IT: Big Data, An Offer That is Formed” (The original article is in French, but http://translate.google.com works well for this gosling). We learn:
As a recognition of the market in 2011, Hadoop has also attracted the top names in the IT industry who put this framework in the heart of their range of data processing volume. One reason: the cost mainly reminded us James Markarian, executive vice president and technical director of Informatica confirming that the framework ‘helped to change the economic model of the Big Data.’ Adding that flexibility… was as a criterion for adoption.
It is clear that the excess of data will only continue to grow by the minute. Generations of search, publishing, and consolidation will continue to emerge. I recommend staying informed of the products and the specific capabilities of each. However, Big Data which is filtered may pose some interesting problems; for example, will the outputs match the pre-filtered reality? Will predictive methods work when some data are no longer in the stream? So far the cheerleading is using chants from an older, pre-filtering era. Is this a good thing or a no-thing?
Andrea Hayden, January 11, 2012
Sponsored by Pandia.com
Inteltrax: Top Stories, January 2 to January 6
January 9, 2012
Inteltrax, the data fusion and business intelligence information service, captured three key stories germane to search this week, specifically, the way many industries are rightfully and wrongfully utilizing analytics.
One of the best stories about traditional industries embracing big data was our story, “Police and Intelligence Communities Share Analytics Needs” which showed how law enforcement and data mining are a match made in heaven.
Slightly further down the scale was our look, “Auto Industry Needs Analytics to Survive,” which showed some small successes in the car industry with analytics and encouraged a wider adoption of practices.
And something completely different came from our article, “Online Reputation Analytics a Mixed Bag,” which chronicled the companies that use analytics to gauge a person’s online reputation and fix it. Our opinion is not so high, however.
This is one of the most exciting aspects of big data analytics. It’s fun to see how established businesses and industries utilize the technology for improvement. At least in most cases (We’re looking at you Reputation.com). Keep up with us as we follow more industry exploits in the world of big data analytics.
Follow the Inteltrax news stream by visiting www.inteltrax.com
Patrick Roland, Editor, Inteltrax.
January 9, 2012
Social Media Analytics Podcast Availalbe
January 9, 2012
Text Analytics News has posted the podcast of their insightful Social Media Analytics Panel. Check it out for a taste of what you can expect at April’s inaugural Social Media Analytics Summit.
The panel brings together Bill Touhig of J.D. Power & Associates, Robin Seidner of Radian6, and Beyond the Arc’s Steven J. Ramirez. The social media analytics experts share their insights in the 55 minute podcast. The description describes the discussion content:
- Analytic technologies and techniques being used to make business sense of the flood of user-generated content
- The cutting edges of social media and sentiment analysis – what works, where improvements are being made, and which platforms are leading the way
- The comparison between proprietary and do-it-yourself tools for social media analysis
- Effective ways for leveraging social media information to get a leg up on your competition
The most memorable points from this podcast for me hinge on the unexpected. Social media is still a very new field that continues to supply surprises. For example, Touhig shared a discovery his company made for a major cosmetics company: trying to stay ahead of the curve, generation Y women were using skin care products made for older women. The company then had to find a way to communicate that using products for their skin type will actually be more effective for these customers.
Another surprise—Ramirez pointed out that, with social media data, more is not better. This may seem obvious to some, but it is not the case with other data types, where more volume produces more accurate results. Instead, analysts find that they need to narrow the data to exclude the vast amounts of irrelevant input that social media provides. As Ramirez commented, “people will say anything!”
It may be no surprise that text analytics is experiencing a talent gap. As Ramirez quipped, if you know young people just starting out, advise them to go into this young field. Yes, general business users are usually capable of analyzing data, but they need a leg-up. It is best to develop a program and invest in tools and training before expecting results from non-specialized employees.
There is much more to this podcast than I can fit here, so be sure to check it out for yourself. Then, plan to attend the Social Media Analytics Summit next spring.
Cynthia Murrell, January 9, 2012
Sponsored by Pandia.com
Mr. MapR: A Xoogler
January 8, 2012
Wired Enterprise gives us a glimpse into MapR, a new distribution for Apache Hadoop, in “Ex-Google Man Sells Search Genius to Rest of World.” The ex-Googler in this case is M.C. Srivas, who was so impressed with Google’s MapReduce platform that he decided to spread its concepts to the outside world. Writer Cade Metz explains,
In the summer of 2009, [Srivas] left the company to found a startup that takes the ideas behind Google’s top-secret infrastructure and delivers them to the average business. The company is called MapR, after Google’s MapReduce, and like so many other companies, Srivas and crew are selling a product based on Hadoop, an open source incarnation of Google’s GFS and MapReduce platforms.
Srivas had the chance to get in on the ground floor of Cloudera, but he was unhappy with that project’s emphasis on support, services, and software add-ons. Instead, he wanted to directly address the core problems with the Hadoop platform. Shortly thereafter, MapR was born.
The article details some of the Hadoop hitches that MapR is addressing. We admire the drive to get to the root of the problems, rather than surrender to the temptation of shortcuts.
Cynthia Murrell, January 8, 2012
Sponsored by Pandia.com
IBM: Buy Them All?
January 3, 2012
In an effort to keep up with technology and their customer base IBM has gone on quite a shopping spree this past year. The article, IBM Acquires Emptoris Analytics, on Network Computing, spotlights the purchase of Emptoris, a leader in supply chain solutions, and highlights other major purchases the software-giant has made in the past two years.
As for the reason for all this purchasing the article explains,
Having established itself as a leader in the market for infrastructure software, IBM is now branching out into application-like products in an effort to maintain growth. Just last week, the company announced that it had reached a definitive agreement to acquire DemandTec, a San Mateo, Calif.-based developer of cloud-based applications for retailers and marketers. Under that agreement, IBM will pay $13.20 per share, or about $400 million, to purchase DemandTec outright.
As IBM rounds out its newly acquired buy-out portfolio we have to wonder if anything substantial will be shown for all the effort and money spent. They claim their focus is on developing software and platforms that put the customer in the center of business. It is obvious after examining the companies bought that IBM is moving in the cloud direction and with the addition of risk analysis companies like Algorithmics will be broadening their customer base and offering top-of-line technology through their software. IBM’s approach may be to buy them all.
Catherine Lamsfuss, January 3, 2012
Sponsored by Pandia.com
Inteltrax: Top Stories, December 26 to December 30
January 2, 2012
Inteltrax, the data fusion and business intelligence information service, captured three key stories germane to search this week, specifically, ways in which some are misusing big data analytics in the market today.
One story, our feature this week, “Real Estate Market Missing Out on Analytic Help” detailed the many ways in which the housing market could be aided by analytics, but is not taking advantage of.
One of the most important stories we’ve written was “Consumer Analytics Not a Strong Investment” which helps analytic software buyers avoid limited programs that will be no help to them.
Finally, we focused on how a lot of cloud analytic offerings don’t make security and customer service a priority in our story: “Accountability Should Be Top Priority for Cloud Analytics.”
Usually, we focus on the uplifting, exciting side of this growing market. However, big data analytics also has its downside, which deserves some light. We try and keep our coverage balanced, in order to give our readers the best overview.
Follow the Inteltrax news stream by visiting www.inteltrax.com
Patrick Roland, Editor, Inteltrax.
January 02, 2012
Digital Reasoning: A New Generation of Big Data Tools
December 31, 2011
I read “Tool Detects Patterns Hidden in Vast Data Sets.” The Broad Institute’s online Web site reported that a group of researchers in the US and Israel “have developed a tool that can tackle large data sets in a way that no other software program can.”
What seems exciting to me is that the mathematical procedure which involves creating a space and grids into which certain discerned patterns are placed provides a fascinating potential enhancement to companies like ours–Digital Reasoning. Our proprietary methods have performed similar associative analytics in order to reduce the uncertainty associated with processing large flows of data and distilling meaningful relationships from them. Some day computers and associated systems will be able to cope with exabytes of data from the Internet of things. Today, the Broad Institute validates the next-generation numerical methods that its researchers, Digital Reasoning’s engineers, and a handful of other organizations have been exploring.
The technical information about the method, which is called MIC, shorthand for Maximal Information Coefficient, is available to members of the AAAS. To get a copy of the original paper and its mathematical exegesis you will want the full bibliographic information:
“Detecting Novel Associations in Large Data Sets” by David N. Reshef, Yakir A. Reshef, Hilary K. Finucane, Sharon R. Grossman, Gilean McVean, Peter J. Turnbaugh, Eric S. Lander, Michael Mitzenmacher, and Pardis C. Sabeti, Science, 16 December 2011, Volume. 334, Number 6062, pages 1518-1524.
The core of the authors work is:
Identifying interesting relationships between pairs of variables in large data sets is increasingly important. Here, we present a measure of dependence for two-variable relationships: the maximal information coefficient (MIC). MIC captures a wide range of associations both functional and not, and for functional relationships provides a score that roughly equals the coefficient of determination (R2) of the data relative to the regression function. MIC belongs to a larger class of maximal information-based nonparametric exploration (MINE) statistics for identifying and classifying relationships. We apply MIC and MINE to data sets in global health, gene expression, major-league baseball, and the human gut microbiota and identify known and novel relationships.
Digital Reasoning’s application of similar mathematical methods underpins our entity-oriented analytics. You can read more about our methods in our description of Synthesys, a platform for performing automated understanding of the meaning of Big Data in real time.
The significance of this paper is that it shines a spotlight on the increasing importance of research into applications of next-generation numerical methods. Public discussion of methods like MIC will serve to accelerate innovation and the diffusion of knowledge. At Digital Reasoning we see this as further evidence of the potential of algorithmic, unaided approaches like ours to achieve true “automated understanding” of all forms of text regardless of volume, velocity or variety. As we shift to IPv6, the “Internet of things” will dramatically increase the flows of real time data. With automobiles and consumer devices transmitting data continuously or on demand, the digital methods of 10 or five years ago fall short.
Three other consequences of MIC-style innovations will accrue:
First, at Digital Reasoning, we will be able to enhance our existing methods with the new insights, forming partnerships and investing in research to apply demonstrations to real world problems. The confidence SilverLake partners’ investment in Digital Reasoning has provided us with capital to extend our commercial system quickly and in new directions such as financial services, health care, legal, and other verticals.
Second, we see the MIC method fueling additional research into methods making Big Data more accessible and useful; that is, consumerize some applications without solutions. Big Data will eventually be part of a standard information process, not something discussed as “new” and “unusual.”
Third, greater awareness of the contribution of mathematics will, I believe, stimulate young men and women to make mathematics and statistics a career. With more talent entering the workforce, the pace of innovation and integration will accelerate. That’s good for many companies, not just Digital Reasoning.
Kudos to the MIC team. What’s next?
Tim Estes, December 31, 2011
Sponsored by Pandia.com
-
- Subscribe to Beyond Search
Feature archive
News archive
-
