The Business Intelligence Blog

Once again, software is fighting crime. Microsoft unveiled a suite of tools and initiatives for law-enforcement groups “specifically designed to improve public security and safety,” the company said.
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It’s also the latest example of law enforcement officials arming themselves with better technology to help fight crime. The FBI, for instance, said that new database and data-sharing efforts have resulted in solving a number of difficult highway serial killings.

Gathering that data is key. That’s why Microsoft this week said it is giving a free tool to INTERPOL called the Computer Online Forensic Evidence Extractor (COFEE), an application that “uses common digital forensics tool to help officers at the scene of the crime.”

The company is working on a mobile version for future release, said Richard Domingues Boscovich, senior attorney for Microsoft’s Internet security program, told InternetNews.com in an e-mail.

A larger tool set for large-scale crimes is Microsoft Intelligence Framework, which is aimed at helping intelligence and law enforcement agencies coordinate information to detect and prevent terrorism, and to solve organized and major crime cases. The framework offers tools for storing and analyzing evidence and information across a variety of sources

From EarthWeb article.

The new version of the SPSS modeling product — the erstwhile Clementine — is now known as PASW Modeler 13; its text analysis product (formerly Text Mining for Clementine) is now PASW Text Analytics 13. SPSS says that, over the course of the year, the rest of the SPSS product line will update under the PASW umbrella — including Statistics and Data Collection.

David Vergara, director of product marketing for SPSS, explains that the change was intended to help customers and prospects understand what the products are doing and how each offering pieces together within the broader portfolio.

Aside from the name change, the new versions of SPSS products focus on usability — and not just for data experts. Wettemann says that SPSS has “recognized that moving beyond the data analyst audience is where you get the real power.” PASW Modeler 13 features a drag-and-drop interface, and functionality that will appeal to business users. Two integral updates include a “comments” tool, in which users can flag notes within the software, and automated data preparation. Data automation mitigates human error and avoids common issues in data quality.

From Destination CRM.

For most of its eight-year history, Cataphora has focused on digital sleuthing. The company hunts for statistical signs of fraud. But in the past few years, Cataphora has been dispatching its data miners into a new market: statistical studies of employee performance.

The trend, though early, is unmistakable, and it extends far beyond Redwood City. Number crunching, a staple for decades in the quantifiable domains of engineering and finance, has spread in recent years into marketing and sales. Companies can now model and optimize operations, and can calculate the return on investment on everything from corporate jets to Super Bowl ads. These successes have led to the next math project: the worker. “You have to bring the same rigor you bring to operations and finance to the analysis of people,” says Rupert Bader, director of workforce planning at Microsoft (MSFT).

Such a mission might have been laughable a decade ago. But as the role of computers in the workplace expands, employees leave digital trails detailing their behavior, their schedule, their interests, and expertise. For executives to calculate the return on investment of each worker, their human resources departments are starting to open their doors to the quants.

From Business Week, an insightful article on how value of each employee is determined by HR using Data Mining/Analytics.

Here’s a follow-up on Reality Mining and Surprise Modelling, which are called as one of the 10 technologies that we think are most likely to change the way we live.

Read more from Forbes.com interview with Sandy Pentland, director of MIT’s Human Dynamics Research program.

Forbes.com: What is “reality mining?”

Sandy Pentland: Reality mining is about using sensors to understand human beings. The sensors could be security cameras, they could be devices that you wear on yourself, they could be cell phones. The point is it’s about people. Data mining is about finding patterns in digital stuff. I’m more interested specifically in finding patterns in humans. I’m taking data mining out into the real world.

What kind of reality-mining experiments have you actually performed?

We developed this thing called a sociometer, a little badge that you wear around your neck that records your body language, your motion and your tone of voice–the tone, not the words. It gives us a nice little package for reality mining.

We’ve done all sorts of interesting things with this. Just listening to peoples’ tones of voice and how they move, we can measure interest level and attention, factors that account for 40% of the variation in the outcomes of things like salary negotiation, dating scenarios, closing a sale, pitching a business plan.

“[We don't] have all the functionality of something like a SAS or an SPSS, because that’s just not our market,” he concedes. It comes down to a difference of scale, Farmer argues: SAS and SPSS typically target larger, more expensive deployments — typically with users well-versed in the usage of their tools. Microsoft is targeting a different kind of data mining consumer: the Excel analyst, for example, who might not have much (if any) experience — with data mining, predictive analytics, or statistical analysis for that matter.

“By the way, I don’t mean to say we can’t hit the high-end. Within Microsoft, we have our own database marketing team. We’re one of the largest companies in the world. We have a huge database marketing team who do classic customer analysis. These guys were all SAS users, but when they joined Microsoft, they started using our tools. The entire process runs on our database, they actually use the Excel [data mining] add-ins to do it. It’s not that there’s nothing they don’t miss, [it's that] they are able to achieve the same business results using our tools.”

Last year, Microsoft released a data mining and predictive analytic add-on for its Excel 2007 product (see http://www.microsoft.com/downloads/details.aspx?FamilyId=7c76e8df-8674-4c3b-a99b-55b17f3c4c51&DisplayLang=en). The add-on, which is similar to Microsoft’s well-known SQL Server BI Accelerator products, integrates natively with Excel 2007. It introduces a new “Data Mining” tab that exposes several pre-built functions, including forecasting, accuracy charting, cross-validation, exception highlighting, category detection, key influencers, shopping basket analysis (the last is a SQL Server 2008-only function) and many others.

From an article on ESJ.

From Info Week -

This week, WellPoint — one the nation’s largest health insurers — revealed it’s investing millions of dollars in a three-year project to build such a drug surveillance system in collaboration with the FDA and several academic institutions, including Harvard University, University of Pennsylvania, and the University of North Carolina. The Safety Sentinel System will mine and analyze aggregate claims, lab, and pharmaceutical data from WellPoint’s 35 million members, who generate 1.4 billion “claim lines” of data each year, said Marcus Wilson, president of HealthCore, WellPoint’s medical outcomes research subsidiary, which WellPoint acquired in 2003 and is overseeing the new project.

Seattle Pi’s Venture Blog has the full story from the start to the end.

Farecast was started by University of Washington computer scientist Oren Etzioni, initially bankrolled by Madrona, built with people from local companies such as Alaska Airlines and AdRelevance and, ultimately, acquired by Microsoft.

Though Farecast had multiple bidders, McIlwain said Microsoft was a good fit since the two companies had worked together in the past and had a similar vision for online search. The proximity of the two companies also played a part, he said.

The acquisition follows the merger of Kayak.com and SideStep, the market leader in next generation travel search. That deal led to new opportunities for Farecast, including discussions with Microsoft which heated up in the past 90 days.

“That consolidation presented opportunities for Farecast … partly differentiated because of their predictive capabilities but also because of who they might have been able to align with in the industry to be a strong and differentiated number two, hoping some day to overtake and become number one,” he said.

Madrona has produced a number of hits recently, with the sales of ShareBuilder, World Wide Packets and iConclude.

Also a quick analysis from Motel Fool on this buy -

Microsoft needs more deals like this one, especially if the Microhoo deal comes undone, and the software giant has the means to go shopping. I’ve suggested that Microsoft pursue potential buyout candidates like The Knot (Nasdaq: KNOT) and Bankrate (Nasdaq: RATE) for the same reason that Farecast works. Whether it’s wedding planning, home refinancing, or booking that flight to visit your parents in Chicago, this is the quality traffic that Microsoft and Yahoo! lack right now.

Anand Rajaraman, the co-founder of Kosmix also teaches Data Mining at Stanford. Here’s an interesting note from his blog.

Some of his students are working to crack algorithms for the on-going Netflix “Better Recommendation Logic” Prize of $1 million. Read it !!

Here’s how the competition works. Netflix has provided a large data set that tells you how nearly half a million people have rated about 18,000 movies. Based on these ratings, you are asked to predict the ratings of these users for movies in the set that they have not rated. The first team to beat the accuracy of Netflix’s proprietary algorithm by a certain margin wins a prize of $1 million!

Different student teams in my class adopted different approaches to the problem, using both published algorithms and novel ideas. Of these, the results from two of the teams illustrate a broader point. Team A came up with a very sophisticated algorithm using the Netflix data. Team B used a very simple algorithm, but they added in additional data beyond the Netflix set: information about movie genres from the Internet Movie Database (IMDB). Guess which team did better?

That’s really a great news to the BI world during these dull days of business. I’m sure other companies will start becoming confident on the never understood phenomenon of ROI. Makes a day !!

According to research presented in a new report, “Data Management for Business Intelligence,” 77% of Best-in-Class companies are able to automate the integration of data from multiple sources, compared to 54% of Industry Average companies, and only 22% of Laggards. This capability was identified by respondents as being critical for solving the top business pressure — the need to reduce the time-to-information for non-technical end-users.

Best-in-Class companies are making investments in technology enablers to alleviate this pressure. 82% of Best-in-Class companies are currently utilizing data warehousing software solutions, versus 56% of all other respondents. 80% of Best-in-Class companies are currently deploying Business Intelligence query and reporting tools, versus 47% of all other respondents. Finally, 68% of Best-in-Class companies are currently implementing data warehouse appliance technology (packaged hardware and software solutions) versus only half that number (34%) of all other respondents.

Its interesting that more and more sports associations are starting to use Business Intelligence software to analyze statistics. As Ian Ayres points out in his latest book, Super Crunchers, the competition between the traditional experts and number crunching softwares has ended. And number crunching softwares are being increasingly used by tranditional “intutional” experts to analyze the data better.

These are clearly the days of Data Mining Softwares. This one is about IBM Cognos. Read more -

“Our analysis of player performance is as complex and dynamic as the work of high-powered business analysts in Fortune 500 companies, and we need to use the same robust, flexible interface to achieve reliable results,” said Doyle Pryor, Assistant General Counsel of the MLBPA. “Conducting complex analysis in real-time allows us to improve our planning processes and IBM Cognos TM1 Executive Viewer enables the agents themselves to view reports and perform almost limitless ‘what-if’ scenarios for further analysis of the data.”

“The interface for analysis will provide sophisticated users with the tools they’re familiar with and the ability to quickly modify views and reports with as little effort as possible,” said Doug Barton, vice president, product marketing, Cognos, an IBM Company. “Users of IBM Cognos TM1 Executive Viewer continue to gravitate to its features that provide interactivity, immediacy, and flexibility, which, in turn, enable them to accelerate the management of their business’s performance.”