Turbotodd

Ruminations on tech, the digital media, and some golf thrown in for good measure.

Posts Tagged ‘jeff jonas

(Almost) Live @ Information On Demand 2012: A Q&A With IBM’s Jeff Jonas

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Jeff Jonas sat down last evening with Scott and I in the Information On Demand 2012 Solutions EXPO to chat about privacy in the Big Data age, and also gave a sneak look into the new “Context Accumulation” technology he’s been working on.

You really ought to get to know IBM’s Jeff Jonas.

As chief scientist of the IBM Entity Analytics group and an IBM Distinguished Engineer, Jeff has been instrumental in driving the development of some ground-breaking technologies, during and prior to IBM’s acquisition of his company, Systems Research & Development (SRD), which Jonas founded in 1984.

SRD’s technology included technology used by the surveillance intelligence arm of the gaming industry, and leveraged facial recognition to protect casinos from aggressive card counting teams (never mind the great irony that IBM’s Yuchun Lee was once upon a time one of those card counters — I think we need to have an onstage interview between those two someday, and I volunteer to conduct it!)

Today, possibly half the casinos in the world use technology created by Jonas and his SRD team, work frequently featured on the Discovery Channel, Learning Channel, and the Travel Channel.

Following an investment in 2001 by In-Q-Tel, the venture capital arm of the CIA, SRD also played a role in America’s national security and counterterrorism mission. One such contribution includes a unique analysis of the connections between the 9/11 terrorists.

This “link analysis” is so unique that it is taught in universities and has been the widely cited by think tanks and the media, including an extensive one-on-one interview with Peter Jennings for ABC PrimeTime.

Following IBM’s acquisition of SRD, these Jonas-inspired innovations continue to create big impacts on society, including the arrest of over 150 child pornographers and the prevention of a national security risk poised against a significant American sporting event.

This technology also assisted in the reunification of over 100 loved ones separated by Hurricane Katrina and at the same time was used to prevent known sexual offenders from being co-located with children in emergency relocation facilities.

Jonas is also somewhat unique as a technologist in that he frequently engages with those in the privacy and civil liberties community. The essential question: How can government protect its citizens while preventing the erosion of long-held freedoms like the Fourth Amendment? With privacy in mind, Jonas invented software which enables organizations to discover records of common interest (e.g., identities) without the transfer of any privacy-invading content.

That’s about where we start this interview with Jeff Jonas, so I’ll let Scott and myself take it from there…

A New Style of Analytics: Making Sense of Data Overload

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If you’re in the business of making decisions…or if someone in your business supports you through decision making…then you’ll probably want to take note of an announcement IBM just made to help bolster decision making capability using analytics technology.

“Big data” is the digital convergence of structured and unstructured data. Those organizations that can capture and analyze their data, regardless of what type, how much, or how fast it is moving, can make more informed decisions.

Yesterday, IBM announced new predictive analytics software that automatically correlates and analyzes big data to help clients embed hyper-intelligence into every business decision.

In addition to generating insights on internal data in a matter of seconds, the software measures the impact of social networking channels and factors this information into organizational decision making.

The software represents a new class of “decision management” capabilities that revolutionizes the way organizations gain, share and take action based on information gathered as part of business processes such as marketing, claims processing and fraud detection.

In these, and other data-rich areas – where anywhere from a thousand to five billion decisions are made daily – the software will put forward the next best action to front-line employees ensuring optimal interactions and outcomes.

Driving Repeatable Results With Fewer Resources

Companies across all industries are increasingly under pressure to drive immediate and repeatable results with fewer resources, react more swiftly to rising customer demands, and gain faster insights on business data.

These pressures are challenging organizations to strengthen their approach to decision making, and forcing organizations to act not only corporate policy and gut instinct.

For example, according to a Columbia Business School Center Global Brand Leadership report, 90 percent of senior corporate marketers believe that successful brands use customer data to drive marketing decisions. Yet 50 percent say that a lack of sharing customer data within their own organization is a barrier to effectively measuring their marketing efforts.

Compounding these challenges is the variety, velocity and volume of big data which is growing at record rates. According to IDC, the decision management software market is expected to exceed $10 billion by 2014.

“In today’s marketplace, when a customer says they’re not happy, companies must decide how to react — not later that day, or in an hour, but instantly,” said Deepak Advani, vice president business analytics products and solutions, IBM.

“With these new technologies, winning organizations can embed analytics into under-served areas of their business, empowering all employees to make information based decisions.”

IBM Analytical Decision Management Software

The new Analytical Decision Management software, part of a series of IBM Smarter Analytics initiatives, helps clients apply automated, real-time analytics into any operational data no matter where it resides, and instantly analyze it to uncover trends and expose hidden paths to growth.

As a result, insights can now be automated, socialized and used for predictive decision making.

In a single platform, IBM has combined the power of business rules, predictive analytics and optimization techniques through intuitive interfaces that allow users to focus on specific business problems. The resulting decision can be consumed by existing pre-packaged or custom-built applications, including many applications on the mainframe.

The platform also takes advantage of IBM InfoSphere Streams technology where big data can be analyzed and shared in motion, providing real-time decision making in environments where thousands of decisions can be made every second.

Entity Analytics: Making Sense of Data Overload

IBM is also extending the powerful analytical functionality with the inclusion of its newest entity analytics capabilities. For the first time, businesses can take advantage of entity analytics as part of the decision management platform.

This feature, especially well suited for big data environments, is a unique analytics engine that enables identification and matching for all entities – people, places, or things – making systems smarter as more information becomes available.

Unlike traditional methods, the IBM entity analytics capabilities are context based and accumulate knowledge, resulting in a more accurate picture, better models, and better outcomes. This ability to understand how the data is related delivers higher quality models and helps to ultimately produce smarter decisions.

Understanding Social Relationships and Influencers

A new social network analytics feature enables companies to take sentiment analysis a step further by analyzing who the influencers are around any given topic, who exactly is listening, and why people should care.

This feature enables decision makers to factor in how customers behave, what they say, and how big their sphere of influence is in a social network.

For example, which other customers does this person know? Does this person influence others in their social network? The ability to incorporate social network analytics into the predictive models used in analytical decision management helps organizations identify social leaders who can influence behavior.

C Spire: Predicting Customer Behavior

IBM client C Spire, a leading telecommunications service provider, is using IBM analytics to get closer to their customers by better predicting customer behavior and intervening before a problem ever arises, making their service and experience more personalized.

“The benefits we are able to see from using this advanced IBM analytics technology will give us the ability to put the right message in front of the right customer at the best time and in the best channel,” said Justin Croft, manager marketing campaigns and promotions, C Spire.

“We will now be able to deliver true personalization, giving the customer exactly what they need, without having to ask for it. Not only does this improve the customer experience, it also positively impacts sales and customer retention.”

This recent announcement builds on the recent release of IBM’s operational decision management software, and represents the first time that both analytical and operational decision management are provided to clients jointly on one platform.

IBM: Laser Focused on Business Analytics

The news is part of IBM’s larger focus on business analytics and optimization, which spans hardware, software, services, and research. IBM projects $16 billion in business analytics revenue by 2015.

To meet that target, the company has established the world’s deepest portfolio of analytics solutions, growing its business and industry expertise to approximately 9,000 business analytics and optimization consultants and 400 researchers, and created global analytics solution centers in Berlin, Beijing, Dallas, London, New York, Tokyo, Washington and Zurich.

IBM has acquired more than 30 companies to build targeted analytics and information expertise and continues to expand its ecosystem, which today consists of more than 27,000 IBM business partners. IBM has also secured hundreds of patents a year in analytics.

These investments have enabled IBM to develop breakthrough technologies like IBM Watson, a new class of industry specific analytical capability that uses deep content analysis, evidence-based reasoning, and natural language processing to identify relationships buried in large volumes of data that can be used to improve decision making.

Go here to learn more about IBM’s Analytical Decision Management technology.  You can also following the ongoing discussion around IBM and entity analytics on Twitter via the following hashtags:  #smarteranalytics #ibmbigdata and #decisionmgmt.

Information On Demand 2011 Live: Opening General Session — Data Puzzles

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This morning’s opening general session at Information On Demand 2011 here at the Mandalay Bay in Las Vegas, Nevada, was jam packed, both in terms of stage setting for the rest of the event, and literally in the audience, which filled up much of the Mandalay Bay Events Center.

BBC America presenter Katty Kay was our host, and opened morning’s tidings with a wonderful video and photo montage that she provided the voiceover for, explaining how IBM innovations had helped change our world over the past 100 years (remember that 2011 is the year of IBM’s centennial).

BBC America presenter Katty Kay kicks off Information On Demand 2011 this morning in Las Vegas, Nevada.

There were pictures and reminiscing about IBM’s Social Security Administration contract, the early days of data processing, the IBM 350 Ramac, the introduction of sequel databases and CICS, and even a remembrance of the floppy disk.  Ah, I remember those well.  They make great coasters.

Kay explained that the pace of computing has only accelerated, the advent of the Internet and the birth of e-business paved the way to our global connectivity, and the smarter planet initiative from IBM is poised to help companies and organizations around the globe maximize their resources and be more socially responsible.

Considering the financial meltdown of 2008, which journalist Kay didn’t gloss over, companies also need guidance and direction to help them with their analytical capabilities, particularly in an age when 1B Tweets are posted a week, and 90% of the world’s information was gathered in only the past two years.

Enter Jeff Jonas, IBM chief scientist who was most recently featured in this fascinating TV commercial about skating to where your data puck is going to be, NOT where it was five minutes ago:

IBM Chief Scientist Jeff Jonas explains the intricacies of information insight vis a vis tabletop puzzles.

Jonas explained that organizations are getting dumber as more data arrives, but that that’s not a fait accompli, that it’s not a foregone conclusion that your organization will have enterprise amnesia.

He started with the video of a blackjack dealer, who was clearly taking a stacked deck from a player, a dealer whom, if the casino had better information, would have discovered that said customer and said dealer had the same home address.  That casino would later go on to get taken for $250K!

Here’s a retail example Jonas shared: 2 out of 1,000 employees employed in retail have already been arrested for stealing at the very same store.  Yikes!

Jonas went on to explain that good information understanding and analytics means context: Better understanding something by taking into account the things around it.

He used, as his example, a series of jigsaw puzzles he had his girlfriend’s kids put together, but having strategically taken some of the pieces of each out.  Even with the missing pieces, the kids were able to get a picture of what the puzzles were about, revealing necessary context.  But until you take the pieces to the table and attempt assembly, Jonas explained, you don’t know what you’re dealing with.

And that’s where many organizations are today.

Incremental Context provides incremental discovery, and given sufficient observations, there can come a tipping point when confidence improves while computational effort decreases.

Put that in your database pipe and smoke it!

Next, IBM’s managing partner of financial services, IBM Global Business Services, Sarah Diamond took the stage to explain how dire the banking situation was in 2008-2010.  The number of bank failures went from 25 in 2008, to over 157 in 2010.

Eventually, the IMF calculated that the banks wrote off $2.2 trillion in toxic assets and bad loans, and emerging from that mess many banks recognized their need to change, to respond to pressure from regulators and their public constituents to better manage risk, and their overall businesses.

IBM customer SunTrust, was one of those banks which were better prepared for the crisis than many, in that they had put together a risk analytics and governance regime before the crisis occurred.

As their senior VP of risk technology explained, SunTrust went from standardized reporting to client-centric reports delivered via intranet portals in just a few short years, and when the financial crisis hit, SunTrust was prepared to know exactly what their exposures were, what they consisted of, and most importantly, who was on the other end of the transaction.

This allowed them to report to senior management on a daily basis at 7 am exactly what their positions were based on their trading partners’ exposures.

If only all banks had been so well prepared.

Written by turbotodd

October 24, 2011 at 5:59 pm

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