From all outward appearances, Cambridge, MA-based data warehousing appliance maker Dataupia and its founder Foster Hinshaw have both been through near-death experiences this year. Heart problems forced to Hinshaw to step down as CEO in January. Dataupia’s board brought in not just a new leader, Tony Sirianni, but a new strategy, concentrating on selling software rather than integrated hardware-software packages.

But the strategy didn’t seem to be enough to stave off the effects of the recession: by June, as we reported, the company had laid off the majority of its staff and was seeking new financing in order to stay alive. In August, reports surfaced that the company had been reduced to a skeleton crew and was selling off its assets. Many database industry observers put the company into the dead pool.

But appearances can be deceiving. Hinshaw is back as CEO, the company’s workforce has stabilized at about 30 (half the number from one year ago), and the startup’s difficult period is behind it, according to an announcement set to be released tomorrow. “After taking a hiatus following a medical surgery, [Hinshaw] is back to lead the Company into a high growth phase,” the announcement says.

That “hiatus” language is a bit of a gloss on the actual situation, which I understand much better after having spoken with Hinshaw himself at length today. Most importantly, Hinshaw—who is widely considered to be the father of the data warehousing appliance business—says that he has fully recovered from coronary artery bypass graft surgery. “I’m out hiking now and doing my normal stuff, which is beautiful,” he says. “It was a long recovery, but it’s amazing what they do.”

But Hinshaw also says that while the recession caused some bumps for the company, including the big wave of layoffs, the rumors about Dataupia’s troubles were far out of proportion to reality. “I don’t want to quote Mark Twain, but some folks on their way out may have said some things that were very hypey,” he says.

Like Hinshaw’s previous company, Netezza (which went public in 2007), Dataupia started out selling data warehousing appliances—very fast servers preloaded with the software needed to help companies such as wireless operators sort through terabytes of historical customer data to discern patterns and extract intelligence. And with Hinshaw back in the saddle, that is once again the company’s emphasis.

But under Sirianni’s leadership, Hinshaw explains, the company steered for a while toward selling the software designed for Dataupia’s hardware as a standalone product. The attraction of this strategy was that it necessitated much lower research and development costs, Hinshaw says.

“With an appliance, you can drop it into a customer site and literally within days you are up and running, which is a powerful story, but the R&D costs are fairly high,” he says. “So there is always the question of whether you want to spend on that R&D, or just take the software and let the customer do the integration” into their existing IT systems.

Whether or not the software strategy was justified, it didn’t boost sales in the way the company would have liked, Hinshaw says. A horrid economic climate was at least part of the problem. “I’m not saying that Tony or the board did a bad job. I interviewed Tony myself,” he says. “But the economy certainly didn’t help any of this stuff.”

While there’s ongoing debate within the industry over the “tools” versus “appliances” question, Hinshaw says he’s personally convinced that …Next Page »

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10gen, a New York-based startup developing the open-source database MongoDB, has raised $3.4 million in Series B venture backing from Boston’s Flybridge Capital Partners and returning investor Union Square Ventures, Flybridge said yesterday. MongoDB is similar to Google’s BigTable and is considered one of the leading examples of non-relational or “NoSQL” database, designed to be sliced up into many parts and implemented across a large computing grid. “We believe MongoDB has the ability to become the predominant platform for web application development,” said Flybridge general partner Chip Hazard in yesterday’s announcement.

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The first meeting of the Boston Big Data Summit was held yesterday. Since the announcement on October 2, the event has had a great reception. Just over a hundred people attended, with an almost even split between “end users” and “vendors.” By a significant margin, the vendors were entrepreneurs or self described “startup types.” Many established players were also represented in the audience.

The program featured a keynote speech by Curt Monash, a leading analyst and strategic advisor to the software industry. This was followed by a lively panel discussion with Ellen Rubin, founder and vice president of products at Cloudswitch; David Cohen, chief architect for the Cloud Infrastructure Group at EMC Corporation; and Larry Dennison, president and founder of Lightwolf Technologies.

The Boston area has long had a tradition of nurturing entrepreneurship in “big iron” and enterprise class products, and the audience yesterday reflected that tradition. Late in September, Bob Zurek and I met to discuss the possibility of setting up this forum. We recognized that there were no technical forums that were geared towards Database Management Systems (DBMS) and Information Management (IM) professionals in the Boston area, and felt that there was an acute need for one.

In setting up the Boston Big Data Summit, we had a simple mission: to create a technical forum for DBMS and IM professionals, and foster innovation and entrepreneurship in these areas, through networking, debate and the sharing of experience. The forums would necessarily be somewhat geeky (that’s what you get when you have two geeks running the show).

The goal was to make them accessible to everyone at no cost. Our sponsors Foley Hoag, Infobright, Expressor Software, and Kalido made the event possible, and we intend to continue to fund this venture through corporate sponsorships.

Yesterday’s event is, hopefully, the first of a regular series of events that we will be organizing. The next event is scheduled for sometime in January, and we would like the one after that, in the spring, to be a day long event with multiple speakers, panelists and discussion areas. The excellent reception to yesterday’s event is a clear indication of the need in this area.

The keynote speech reflected Curt’s extensive experience and depth of knowledge in the field of Big Data, analytics, and the companies and technologies in the space. Curt described the market and provided three different ways of segmenting the market for these products, a segmentation that was the subject of much discussion after …Next Page »

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Raveable is a year-old Seattle-area startup that launched its hotel review summarization website in May. If there were a Raveable entry for Raveable itself, here’s what it might say:

Ranked 116 out of 340 tech startup websites in Seattle.

The good: Team is ambitious and knowledgeable; large market; useful technology; fun interface; customer focused; strong word of mouth.

The bad: Relatively new; pre-revenue company.

Best kept secret: Gaining attention from angel investors and VCs.

The idea of Raveable is to help leisure travelers quickly make sense of all the user reviews out there on the Web, and choose a hotel that’s right for them. So the company aggregates reviews from sites like TravelPost (Kayak), MyTravelGuide (Priceline), CitySearch, Yahoo Travel, and VirtualTourist, and provides a bullet-point analysis of the pros and cons of each hotel—for 55,000 establishments and counting in the U.S.

The company was founded by Philip Vaughn and Rafik Robeal, former Microsoft veterans with expertise in database applications, data synchronization, and mobile social networking. Raveable grew out of difficulties they’d each had in booking hotels quickly; they found they were sorting through dozens of reviews on multiple sites, without having a top-down view of how various hotels stack up against each other.

“We want to make it really easy to make a decision,” Vaughn says. “We were really frustrated by ‘Everything is 3.5 stars, everything is above average, everything is good.’”

The technology behind their approach is semantic analysis of text—an area that’s been in research for decades, but is increasingly being applied to Web search and corporate software. The goal is for the software to understand the meaning of sentences in user reviews—including the topic, the context, and the sentiment. So if reviews say the rooms are great, beds are comfortable, or parking is expensive, that’s pretty straightforward. But if they say the service could be faster, rooms get cold, the view is sick, or the place is in good need of repairs, say, the software relies on statistical models (trained and updated by the founders) to ascertain whether the sentiment is positive or negative.

Vaughn gives a sense of historical perspective, pointing out that Raveable fits into the trend …Next Page »

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According to regulatory documents filed yesterday, stealth Boston startup Akiba has closed a $6.53 million Series A venture capital round with participation by North Bridge Venture Partners and Foundation Capital. The company describes itself as developing a virtualization technology that makes it easier to manage relational databases in cloud-computing environments.

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Dan Weld spends a lot of time thinking about the Web and how to get the best information out of it. Weld is a professor of computer science and engineering at the University of Washington and a serial entrepreneur, having co-founded Netbot, AdRelevance, and Nimble Technology. He is also a venture partner with Seattle-based Madrona Venture Group. Some of his research projects include customizable software interfaces and ways to improve information finding on Wikipedia. He is an expert in Web search, information extraction, and adaptive user interfaces, so he seemed like the perfect person to ask: what is the big deal with Microsoft’s Bing, anyway?

In a recent interview, Weld talked about the improvements Bing has made over Google and other current search engines (only slight), the future of Web search, and a hint at a project he is working on that he thinks could change the way we find information online.

The following is an edited version of our conversation.

Xconomy: Let’s start with your general impressions of Bing.

Dan Weld: I think it’s a nice, if small, advance. Some of the things they’ve done in this relaunch are primarily architectural and will support their plans for the future. In terms of what is actually available right now, the biggest change is integrating vertical search in a uniform way.

X: What does that mean?

DW: When you think of search, everyone thinks about Google, and maybe Yahoo, but there are many other kinds of search, like people searches (you can think about Facebook as a people search), travel search (Kayak and Expedia), health information sites. You can think about Wikipedia as providing a search for encyclopedic information. Shopping searches—Amazon is great in part because it makes it easy to find so much information about the products, and reviews of products. All of these are examples of vertical search experiences. Instead of having wide coverage, you have a better experience within a narrow range.

Bing has tried to marry those things into an integrated wide search experience. All of the engines have been doing this. If you do a search on Google for a movie, you might see information about show times and trailers at the top, for example. Bing has gone further in some directions than people have gone before, in this aspect. If you look at their tabbed pane, it lets you look at different kinds of information right there.

X: But doesn’t Google do that too?

DW: All the engines are trying to do it, but the way Microsoft has done it with Bing is somewhat better than what Google has done. With the shopping tab, you get a faceted interface, meaning you can narrow your search using categorical information, restricting yourself to a particular brand or price range. Those facets are specific to the object you’re searching.

X: So if this is just a small change, what kinds of big changes can we expect to see in the future?

DW: Lots of people are happy with search today, but that’s because they set their sights too low. I think search is going to change enormously in the future, and I think it’s going to do so by …Next Page »

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Bing, Microsoft’s new search engine, is partnering with PayScale, a Seattle-based salary comparison company, to help Bing users find answers about job salaries. Bing debuted last week, and has continued to add new features and capabilities as it attempts to compete with Google and become what Microsoft calls a “decision engine.”

Under the terms of the partnership, salary queries about the 4,000 most popular jobs will be available immediately to people searching on Bing. Those who want more specific information will then be directed to PayScale. Staying on the Bing site, users will be able to access both national and metropolitan figures about salary.

PayScale, which has more than 17.5 million compensation profiles, is the biggest salary database on the Web. Founded in 2002, the company offers a free anonymous comparison of salaries to people who fill out a profile, and a more detailed comparison report for about $20. It also offers software for employers looking to figure out the best compensation and benefits plan for their company.

With more job-hunters using the Internet than ever before, the benefits in increased recognition and popularity for both PayScale and Bing could be enormous, especially if more people turn to Bing, and through it, PayScale, for all of their job-seeking concerns. Those who buy the premium package from PayScale get not just information but analysis and career-planning recommendations.

Working with PayScale may turn out to help Bing in its struggle to compete with Google, as well as in its effort to attract users and advertisers in a recession.

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Waltham, MA-based Xkoto, a database virtualization company that relocated from Ontario, Canada, to Massachusetts in 2007, announced today that it has raised $3 million from existing investors GrandBanks Capital and GrowthWorks Canadian Fund. The infusion brings the four-year-old company’s total venture pot to $13 million. Xkoto was named InformationWeek’s “Startup of the Year” in 2008 and reports a major expansion in its customer base and revenue for the year.

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Acton, MA-based Lumigent, a nine-year-old company long handicapped by a dwindling market for its database auditing software, said today that it has secured $6 million in new funding from Waltham, MA-based North Bridge Venture Partners to help with its new mission of helping companies lower the cost of complying with financial regulations such as Sarbanes-Oxley. The company said the funding will help it market its recently revamped products in the area of compliance auditing for enterprise resoure planning applications such as Deltek CostPoint and PeopleSoft Financials. We’ll bring you more on the story of Lumigent’s turnaround under new CEO John Capobianco later this week.

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A Seattle startup is playing an important role in helping President-elect Barack Obama’s transition team get organized. As of yesterday, the Obama-Biden Transition Project has been using technology from Blist (pronounced as one syllable, and spelled with a lowercase “b” by its employees) to power its Change.gov website. The company’s software lets people create, manage, and publish large, interactive lists and databases—similar to working with a simple spreadsheet, but shareable across the Web.

It’s all part of Obama’s pledge to run an open and transparent White House transition, in part by releasing the names of all its donors on a monthly basis. In his company blog, Blist’s founder and CEO Kevin Merritt says he is “really excited” about the exposure and about what his software can do for Obama’s team. “They are using blist in a simple but useful way,” he says.

Go to the Change.gov site, and you’ll see a Blist widget replacing the plain HTML table of the past two months. The widget lets you sort the donor table by column, such as by city or amount. It also lets you search for things like names and employers. (Out of 53,853 donors, I counted 43 from Microsoft versus two from Amazon, for instance.)

This afternoon, I heard from Jon Byrum, Blist’s senior product manager, about how the collaboration with Obama’s team originally came about, and what it means to Blist. “Last Wednesday—on New Year’s Eve—a member from the Change.gov New Media team contacted us about using a blist Widget to post the Obama campaign donor list,” said Byrum in an e-mail. “He let us know that he was planning to post a press release and web page on January 5th, and wanted to ensure that our servers would be able to handle the load. When we asked how he got started with blist, he said the Change.gov team found us through Google …Next Page »

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Seattle-based Amazon Web Services announced today it is providing free access to centralized data sets in the Internet cloud. The Amazon subsidiary will host large data sets from genomics, bioinformatics, economics, U.S. Census information, and other areas, which researchers and developers can access from the Amazon Elastic Compute Cloud software platform. The effort is intended to fuel innovation, accelerate the pace of new discoveries, and, of course, bring more users into Amazon’s cloud computing services.

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Want to simplify your holiday shopping lists this year? What about keeping track of who’s picking up the kids from the airport, or who’s going to watch the bird in the oven while you entertain guests? A Seattle startup appears to be gaining traction in helping people manage these kinds of tasks. Cozi, a software company that helps busy families organize their calendars, track to-do lists, and stay in touch, announced it has registered more than a million family members on its free Web-based service.

It’s been a busy and productive year for Cozi, as the company has made the jump from personal-computer software to a Web 2.0 service. In the process, it has added some partnerships with big companies like Whirlpool, Unilever, Best Buy, Gannett, and Meredith Corporation’s Better Homes and Gardens brand (just announced yesterday). And in the middle of the year, it began its advertising model and has signed on dozens of companies like Target, American Express, and Universal Studios.

Cozi launched its software product in the fall of 2006 and is backed by just over $16 million in funding, from Gannett and other investors. It was founded by veterans of Microsoft, Expedia, and Amazon. Most of its customers are based in the U.S., but Cozi also boasts users in about 125 other countries. “Reaching 1 million family members confirms the belief we’ve had all along that families will embrace technology to organize their busy lives and to stay connected to each other as long it simplifies rather than complicates family life,” says Carl Weinstein, Cozi’s chief marketing officer.

I asked Weinstein about the challenges associated with increasing numbers of users. “From a technical perspective, this is growth we expected and have been prepared for,” he replied. “We foresee no technical challenges that we haven’t already anticipated at this point. We’ve just finished the final phase of creating a highly scalable database architecture which will enable us to grow well beyond this level of use with little if any R&D overhead. As we add new features, and that is a big priority for us looking forward, we’re always considering scalability and redundancy given the size of our customer base.”

So where does it all go from here? Not surprisingly, Weinstein is upbeat. “This all bodes really well for Cozi in 2009. Our business model is strong, we are heavily focused on new feature development and our research indicates that more families than ever are ready to ditch their old ways of organizing for a modern solution,” he says. “Given that most families, regardless of how much technology they use personally at work or elsewhere, are still using pen and paper to manage the family, we are very excited about our prospects for the future.”

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After 16 months in business, Xconomy has published about 3,400 pages of articles. At this pace, we’ll get to 1.8 million pages in about 700 years. But the Encyclopedia of Life—a new scientific and educational website that will have one page for every species on the planet—intends to hit that number in just 10 years. And even then, it will only be getting started: while biologists have named, described, and catalogued some 1.8 million critters, they estimate that another 8 million species of plants, animals, fungi, bacteria, protists, viruses, and archaea remain undiscovered.

That’s a seriously big website. We’re talking Wikipedia big. (The famous free online encyclopedia, begun in 2000, has 2.6 million articles in English alone, and over 10 million all told.) Which means the organizers of the Encyclopedia of Life (EOL for short) are going to have to throw out the old playbook in taxonomy—the slow and meticulous science of species classification, born 250 years ago this year with the publication of Karl Linnaeus’ Systema Naturae—and turn to the techniques of Web 2.0.

Specifically, they’re going to have to rely on thousands of amateur naturalists to collect and submit data for the encyclopedia. But that creates a fascinating problem: How do you partake of the revolution in “user-generated content,” as Wikipedia has done, while keeping the material you publish wholly factual and stable—as it ought to be if the Encyclopedia of Life is to be a useful resource for scientists, students, and policy makers, and as Wikipedia manifestly is not? I’ve been reading up on the EOL project this week, and as far as I can tell, the organizers haven’t yet worked out a thorough answer to that question.

Of course, not all of the material in EOL will be user-generated. A big part of the concept for the encyclopedia, a $40 million project funded by the John D. and Catherine T. MacArthur Foundation and the Alfred P. Sloan Foundation, is that it will be a classic Web 2.0 “mashup.” You’re probably familiar with RSS news readers, which assemble headlines and stories from hundreds of separate websites; in a similar way, EOL will use Web-based aggregation technology under development at the Marine Biological Laboratory in Woods Hole, MA, to suck in and recompile information from existing online species databases, such as the uBio NameBank, iSpecies, FishBase, AmphibiaWeb, and North American Mammals.

Another big part of EOL involves digitizing millions of print books and journal articles in 10 of the world’s leading natural history libraries, including the Harvard University Botany Libraries and the Ernst Mayr Library of the Museum of Comparative Zoology here in Cambridge (the full list is here). The hope is that once this information has been scanned, run through optical-character recognition software, and automatically tagged with the appropriate metadata, it will be possible to access passages from the scientific literature from the relevant species pages in EOL. Say you’re researching Nicrophorus americanus, the American Burying Beetle—a colorful but critically endangered species for which there’s already a very nice page at EOL. The encyclopedia may lead you to, among other resources, a detailed description published in the Proceedings of the Academy of Natural Sciences of Philadelphia in 1853.

The problem is that scanning, classifying, editing, and mashing together all of that material is going to take years, especially given that it’s all being done on the cheap (EOL and digitization partner, the Biodiversity Heritage Library, have nothing like the amount of money Google is spending on its Book Search project). But “EOL must show some results and value quickly” if it is to be taken seriously by scientists, funders, and the public at large, as the project’s own planning documents acknowledge.

It’s hard to see how the current plan, spelled out in the planning documents and the project’s FAQ page, will accomplish that. Each species page is to have a volunteer “curator,” a competent scientist responsible for authenticating information submitted by contributors before it’s published. Unfortunately, the world population of trained taxonomists is only about 6,000, according to E. O. Wilson, the famed Harvard biologist who conceived EOL and is the project’s honorary chairman. So if you left the curating to the real experts, they’d each have …Next Page »

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It was almost exactly a year ago that Microsoft launched its HealthVault service, a secure online database for users to store and manage their medical records. And in recent months, we’ve reported on the software giant’s increasing efforts in health care, including its new partnerships with prescription drug provider CVS Caremark and Boston, MA-based health startup American Well. Now, Microsoft is teaming up with San Diego-based Scripps Health to study the long-term effects of personal genome testing on health and lifestyle.

The study, which is co-sponsored by the Bay Area firms Affymetrix and Navigenics, seeks to do genetic scans on as many as 10,000 people affiliated with the non-profit Scripps Health system. The scans and analysis will tell participants about their genetic risk for health conditions like diabetes, obesity, heart attack, and certain types of cancer. But the point of the study is to follow what happens after that: will participants change their lifestyle to combat their newfound health risks, and if so, how? The plan is to track their behaviors over 20 years using detailed questionnaires and periodic health surveys. To protect the privacy of users, the identifying information on their saliva samples and questionnaires will be “encrypted and kept in a secure database,” according to Scripps.

What’s in it for Microsoft? Participants will be able to store their clinical and lifestyle information in a Microsoft HealthVault account, and access it or share it with health care providers. “This collaboration is a significant step forward in empowering people to proactively address their specific individual health needs, as well as give clinical researchers access to a broader pool of genetic data to develop new disease treatments,” said Peter Neupert, corporate vice president of Microsoft’s health solutions group, in a statement.

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Apparently it’s a good time to be in the business of data visualization. Wade wrote in July about Visual I|O, a Newton, MA-based business-analytics startup, and Hans Rosling’s splashy Trendalyzer software, which was acquired by Google last year. Not to be outdone, Seattle-based Tableau Software is announcing today it has closed a Series B round of venture financing worth $10 million. The sole investor in the deal is New Enterprise Associates, a leading venture firm based in Menlo Park, CA. Back in 2004, Tableau raised a $5 million first round, also from NEA.

I had a chance to talk with Christian Chabot, Tableau’s CEO and co-founder, and Elissa Fink, vice president of marketing, about the deal, the company, and its plans. For starters, Chabot says that what differentiates Tableau from other data-visualization companies is that, quite simply, it has a viable product that’s easy to download and use. “There’s a lot of excitement right now,” says Chabot. “Business is literally exploding in every area in terms of customer growth.”

Tableau was spun out of Stanford University in 2003, and was funded by the founders for the first year and a half. Its technology, which helps people graphically display and understand information in databases and spreadsheets, originally came out of a Defense Advanced Research Projects Agency-funded effort at Stanford. The project was led by Chris Stolte and graphics researcher Pat Hanrahan, best known for his work on Toy Story with Pixar. Stolte and Hanrahan teamed up with Chabot, who had done his undergrad and M.B.A. studies at Stanford, to found Tableau. (Stanford has an equity stake in the company.)

Chabot explains the significance of his visualization software: “Google has done a fantastic job to allow a human being to sit down with the Web and ask it questions. But the $64 million question is, who’s doing that for data? Databases are baffling…There’s this giant unsolved, planetary-scope problem—how do human beings sit down and have an easy interface to understand data, so they can answer questions?”

Say you want to know where “911″ emergency calls were made in the Seattle area and what they were about, or the amounts of U.S. presidential campaign donations in Manhattan by ZIP code (see screenshot left, and next page). Tableau’s software lets you compile stats from different spreadsheets and databases and quickly graph various slices of the data. The same goes for organizing and displaying things like auto sales trends, population maps, per-capita energy use, and hurricane tracking.

Tableau’s key competitive advantage, according to Chabot, is that its software can be downloaded in two minutes and used without any special training. “The big problems are actually about the user interface,” he says. “It’s easy to install and get started, and easy to get a result from it…What takes unbelievable effort and engineering is to take a complicated problem and make it simple.”

So, coming out of Stanford, how did Tableau end up in Seattle? It was simply a lifestyle decision by its founders—Chabot and Stolte had been in the San Francisco Bay Area for years, and both wanted to live in Seattle. (I can relate to making a move like that.) So in 2004, Tableau moved from Mountain View, CA, to the Fremont neighborhood of Seattle. “It’s a great city,” says Chabot. “It’s clearly no Silicon Valley in terms of sheer volume of technology companies, but …Next Page »

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OK, it’s taken me a few weeks, but I finally have a chance to highlight a couple of entries in a local blog I’ve been following. It’s from the guys at Blist, a Seattle startup that makes Web-based software that lets people manage large lists and databases as easily as a spreadsheet. That may not sound that exciting at first, but the software also lets you share, publish, and collaborate on lists online, and that leads to interesting business applications as well as online communities united around common interests.

In February, Blist raised $6.5 million in first-round financing from Frazier Technology Ventures and Morgenthaler Ventures. The company was founded in early 2007 by Kevin Merritt, formerly CTO of FrontBridge, which was bought by Microsoft in 2005. Recently I’ve found the Blist blog to be chock-full of insights into entrepreneurship, product management, and the local innovation community—all through the lens of a startup on the rise. Two recent highlights:

—Jon Byrum, senior product manager at Blist, wrote yesterday about the importance of truly understanding your customer base. He points out that there is a trap involved in talking to customers one-on-one. You may think you have a good sample of opinions and requests, but the truth is “you don’t have an understanding to the extent to which the requests are important, or how strongly they are affecting your total customer base,” he writes. What’s more, product managers (like everyone else) are susceptible to confirmation bias, whereby you have a gut feeling that users want a certain feature, and when you hear a few of them confirm this, you inflate the importance of that small sample.

The solution? Work to overcome such biases, and complement talks with customers with much larger and more comprehensive samples of user data. Only then, Byrum writes, will you truly understand how to focus your limited resources of engineering time and brainpower. I suspect the lesson applies in principle to a lot of other scenarios as well: managing a large team, planning marketing strategies, and understanding your audience as a blogger, to name a few.

—Kevin Merritt, CEO of Blist, wrote last Thursday about his proposal for how Microsoft can stay on top. You’ve got to read the whole post—it’s got some great specifics—but let me just summarize a few nuggets here. “It will require the Redmond giant to return to their risk taking, entrepreneurial roots. Insiders at Microsoft call it making big bets. It’s time to make some big bets,” Merritt writes. The gist is that Microsoft should start a venture fund. (Merritt points out that he had the idea before Google announced its own fund last week.) In short, he thinks Microsoft needs to start investing in small startups, similar to the Y Combinator program in Boston and the Bay Area, in exchange for stock and the startups’ commitment to using only Microsoft development software, operating systems, and product platforms.

Merritt suggests the Microsoft investment committee should consist of Ray Ozzie, Don Dodge (who recently posted for Xconomy here), and Dare Obasanjo. Proposals should be reviewed once a quarter, in 90-minute demo-and-pitch sessions. At the end, you are either in or out, “American Idol style.” If you pass, your company gets up to $175,000, plus Microsoft IT support and software, and office space.

From a distance at least, it makes good sense. Microsoft has tons of cash—annual revenues of $60 billion, net profits of $17 billion; each is triple that of Google. Merritt argues that if they take on 100 companies each year—which seems like a huge number to me—it should cost only about $25 million, a drop in the bucket of Microsoft’s R&D budget. Realistically, I could see them starting with a handful of companies, maybe 10 or 12; 100 is too many for a venture organization to do a meaningful evaluation. But what’s interesting to me is that it’s all about Microsoft seriously tapping into the innovation community—something I agree the software giant needs to do to not only stay relevant but dominate in the decades to come.

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In February 2006, Swedish physician, statistician, and global health expert Hans Rosling brought down the house at TED (the Technology, Entertainment, and Design conference in Monterey, CA) with a presentation on health and economic trends in developing nations. But it wasn’t the content of the presentation so much as the software he was using that grabbed the audience: called Trendalyzer, the program converted Rosling’s data into colorful animated graphs. By representing countries as dots of varying size that moved against the x and y axes over time, Trendalyzer brought vivid life to changes such as the last century’s general improvements in income and life expectancy—and highlighted how health and wealth in once-lagging regions such as Asia have surged ahead, while they have improved much more slowly in areas such as sub-Saharan Africa.

To many in the audience (and to me, when I watched the online video of Rosling’s TED talk), the Trendalyzer presentation was a revelation, seemingly heralding a new era in which clever design choices coupled with serious graphics-processing power would cause all sorts of interesting trends in complex data to leap out at computer users. Indeed, the next year, Google announced that it had acquired the Trendalyzer software from Rosling’s non-profit Gapminder Foundation, saying that it hoped to improve and expand Trendalyzer and make it “freely available to any and all users capable of thinking outside the X and Y axes.” Unfortunately, like many other early-stage technologies that get anointed by the massive buzz amplifier that is TED, Trendalyzer has since receded from view. Google hasn’t done much with the software, beyond making a Trendalyzer-like gadget called “MotionChart” available as part of Google Spreadsheets.

Meanwhile, there’s a company in Newton, MA, that has spent the better part of this decade quietly applying many of the same design principles behind Trendalyzer to business problems—and selling its software, to boot. It’s called Visual I|O, and I spent some time recently learning about the company’s remarkably beautiful Web-based business analytics software, called DecisionIris, from company co-founder, president, and CEO Angela Shen-Hsieh.

Now, that’s probably the first time I’ve ever used “beautiful” and “business analytics software” in the same sentence. While Visual I|O markets DecisionIris as a business intelligence tool, and making sense of complex business data is certainly one of its strengths, it would be grossly unfair to lump the program in with the kinds of graphical tools offered by traditional business intelligence companies like SAP and Cognos, which are closer to the primitive chart wizards in Microsoft Excel than to anything a professional information designer might conceive. If you’re an aficionado of the work of Yale information designer Edward Tufte—author of The Visual Display of Quantitative Information and Visual Explanations and the man the New York Times has described as “the da Vinci of data”—then you will immediately feel at home with the way DecisionIris represents logical relationships and changes over time, and with the innate sense of color and proportion built into the software.

I’m gushing, I know, but bear with me. The program’s beauty is undoubtedly traceable to the fact that Shen-Hsieh and her fellow co-founder Mark Schindler are both Harvard-trained architects, not software engineers. The pair created Visual I|O as a spinoff of Chicago-based consulting firm Schindler + Associates (where Mark was a partner) in 2002; they wanted to take the visualization software the firm had created to help clients such as pharmaceutical companies get a high-level view of their data and turn it into a commercial product.

Shen-Hsieh (pronounced “shen-shay”) and Schindler felt sure that there was a larger market for software that would help business managers visualize data more flexibly—switching between space-based and time-based representations, for example—depending on the kinds of insights being sought. After all, why go the trouble of collecting terabytes of data about a company’s performance and assembling it into huge, expensive databases and data warehouses if you can’t play with it at will? “If you look at the history of information technology, so much of it is focused on storing and accessing data,” Shen-Hsieh says. “We focus in the last 18 inches–from the screen to the brain. We’re about the cognitive piece.”

Since a picture equals one kiloword, I’ll refer you at this point to the picture at right. It’s a screen shot from a demo Shen-Hsieh walked me through, based on real data about residential properties for sale in the Boston suburbs of Brookline, Newton, Waltham, and Watertown. It illustrates how DecisionIris can help users draw meaning from a mess of data by bringing out multiple dimensions of the data simultaneously; an example about real estate seems easier for most people to relate to than heavy business analytics. (Click on the picture for a larger version.)

Each dot in the chart represents a house. The size of the dot represents the house’s asking price, and its color shows which town it’s in—Brookline is purple, Newton is blue, Waltham is green, and Watertown is yellow. The horizontal axis indicates the year the house was built, and the vertical axis indicates its square footage. (Notice how that’s already four dimensions of data, packed into a type of graph usually used for no more than two dimensions.)

What observations can be drawn from the chart? Well, right away, it’s obvious that houses for sale in Newton are older, bigger, and more expensive than houses in the other cities. That makes sense, given that Newton (where Visual I|O happens to be located) was one of Boston’s first major suburbs, and is still home to …Next Page »

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Cambridge, MA-based Good Data wants to do for business intelligence software what Salesforce has done for customer relationship management: put it on the Web and make it easier to use. In theory, that will give more people in an organization the ability to spot business trends and make informed decisions. Today, the 30-person Web 2.0 startup announced that it has collected $2 million in seed funding to test that theory, by turning its prototype into a full production system.

The money comes courtesy of tech-celebrity investors Esther Dyson and Tim O’Reilly, as well as Good Data founder and CEO Roman Stanek and New York-based VC firm Windcrest Partners. Good Data’s focus is “delivering bite-sized, use-as-you-go data analytics that will actually get used by normal people,” Dyson said in a statement announcing the investment. (It’s the third time Dyson has invested in a company headed by Stanek; the first two were Java programming company NetBeans and enterprise software infrastructure provider Systinet.) “I think of it as the data equivalent of an ATM: You can get the value out when and where you need it.”

“Business intelligence” or BI is the general term for the layer of software tools programmers have developed to make sense of, and help executives make decisions based upon, the untamed morass of data that most big companies collect in their transaction-level databases—for example, sales data from a chain of retail stores. The Boston area is a hub of sorts both for BI toolmakers (IBM’s Cognos division, Metatomix, Visual I|O) and for builders of the data warehouse software and appliances that often intermediates between transaction-level databases and BI interfaces (Kalido, Netezza).

Good Data is trying to set itself apart from all of these companies by combining the data-warehousing and business intelligence functions into single service, and offering the whole thing over the Internet, using the Software-as-a-Service (Saas) model pioneered by Salesforce and others. While its software isn’t yet available, a demo on Good Data’s site shows how users can upload raw data to the company’s cloud of servers, then experiment with different ways of arranging, filtering, and visualizing the data using simple, Web-based drop-down menus and drag-and-drop buttons. In the fictional case study used in the demo, a marketing executive is able to sort through historical sales data from a chain of convenience stores to identify the most effective promotional events at each store.

Overall, the analytical part of Good Data’s system seems to work a lot like Microsoft Excel or Google Spreadsheets, but with an attractive Web 2.0 pastel color scheme and, more importantly, built-in mechanisms for workers to access data from their Web browsers and to annotate and share their insights—for example, by saving custom graphs or tables that highlight interesting trends. (Good data is promoting the term “collaborative analytics” to describe this process. Click on the images at left for bigger views of Good Data’s user interface.)

As the company’s software engineers, who are mainly based in the Czech Republic, use the seed funding to get the Good Data tools ready for rollout, the company is collecting names of volunteers for an upcoming hands-on preview.

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Venture financing deals have been slow going into the dog days of summer. But today Xeround, a software startup based in Bellevue, WA, announced it has closed a Series B funding round worth $16 million. Ignition Partners and Trilogy Partnership, both also in Bellevue, led the round and were joined by previous investors Benchmark Capital and Giza Venture Capital.

Xeround (whose logo looks a lot like Ignition’s) develops cloud-computing software to help businesses, primarily in the telecommunications industry, manage their data. In three years of R&D done in Israel, Xeround has come up with what it calls an “intelligent data grid” that allows customers to put all their information (such as subscriber data) in one place, instead of having it scattered across multiple databases—and access it quickly even as the amount of information grows. Xeround is currently deploying its data grid for a few unnamed customers, working with partners such as Sun and IBM. The investors are banking on the idea that telecoms and cable companies will need more and more innovative ways to find and manage their subscriber base—probably a good bet.

Xeround will use the funds to broaden its reach in North America and Europe and to support sales, marketing, and product development, said CEO Charlotte Yarkoni in a statement. “Our business model and approach to data management will continue to provide a truly unique market offering that delivers the performance, scalability and flexibility to support numerous applications in the telecommunications industry and beyond.”

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Netezza (NYSE: NZ) sells high-performance data warehousing appliances to companies such as Neiman Marcus, Amazon, and TJX that need to analyze terabytes of customer data quickly to detect fraud or help with marketing decisions. Thanks to new compression techniques being rolled out next month as part of the latest software upgrade for Netezza’s appliances, they’ll be able to sift through that data more quickly, and store more of it.

“These are big companies with datasets that are growing 20 to 50 percent annually,” says Phil Francisco, vice president of product management and marketing at Framingham, MA-based Netezza, which went public last summer in one of the Boston area’s biggest technology IPOs. “The ability to make that data actionable in a low-latency way [i.e., faster] has become a fundamental competitive lever in their businesses.”

Data warehouses are like staging areas for the raw information sitting in the transaction databases large companies manage to compile data on sales, customers, suppliers, and employees. The business intelligence software used to make sense of all this data can’t query the transaction systems directly, since they store data in many different formats. Data warehouse appliances extract the information and store it in a uniform way.

The new “Compress Engine” feature of Netezza’s servers, unveiled yesterday, will double the speed at which that stored data can be extracted from the devices’ disk drives, while at the same time allowing companies to store four or more times as much data on each machine. And all of that will be achieved through a simple software upgrade—one bonus of Netezza’s hardware-intensive approach to data warehousing, in which each storage server is actually a powerful computer containing special chips assigned to speed query-answering by filtering out irrelevant data as it streams off of hard drives.

Netezza calls those custom chips “FAST Engines.” FAST Stands for FPGA Accelerated Streaming Technology; FPGA, in turn, stands for Field Programmable Gate Array, connoting the fact that the chips aren’t designed for any specific application but can be reprogrammed on the fly to carry out any logical function. With the software upgrade, Netezza is assigning a portion of each FAST Engine just to handle data decompression, which is normally a CPU-intensive task that slows down everything else. “We’re able to do decompression at the same rate that we read the disks—so if your data is compressed at a 2-to-1 ratio and the read rate of your disk drive is 60 megabits per second, effectively we’re hitting a scan rate of 120 megabits per second,” explains Francisco.

In the end, that means companies can get answers to crucial business questions faster. (Netezza has a fairly informative blog post about the whole thing.) The new technology will be an optional feature available to Netezza customers for an extra fee as part of the 4.5 release of the Netezza Performance Server software.

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