A couple of interesting notes today….  On the PRNewswire today, Kontagent, a leading enterprise user analytics company, today announced that it has closed $12 million in Series B financing with a consortium of investors including Battery Ventures, Altos Ventures, and Maverick Capital.  Kontagent focuses on social and mobile web applications with their kSuite product, which combines a proprietary database with customized analytics and real-time monitoring to help customers identify and react to usage patterns in real-time.  This continues the pattern of heavy entry level funding into analytics and big data startups – data science applications are becoming the next big technology boom…

There’s another interesting article snippet at Bloomberg Businessweek about how the oncoming avalanche of data could change the nature of astronomy and physics.  According to the article, Johns Hopkins will be building a 100 gigabit-per-second network to shuttle data from the campus to other large computing centers at national labs and even to Google.  Here’s what Dr. Alex Szalay, Alumni Centennial Professor at Johns Hopkins and head of the network project, thinks about what this could mean for the future of science itself:

In his mind, the new way of using massive processing power to filter through petabytes of data is an entirely new type of computing that will lead to advances in astronomy and physics, much as how the microscope’s creation in the 17th century led to advances in biology and chemistry. In that light, the creation of a 100 gigabit-per-second research network at Johns Hopkins becomes not just a fast network but also an essential tool for research and discovery, a basic component of the 21st century microscope.

You can read about the Kontagent financing deal here, and Dr. Szalay’s effort to build big data networks here…

I ran across this post on Analyst First by Stephen Samild, where he describes the world of Business Analytics as a prime area for the Lean Startup model.

I am a big fan of Eric Ries’ book The Lean Startup, where he advocates treating every new entrepreneurial venture, whether inside an existing company or as its own startup company, as a startup.  And further, since this is a startup venture, the uncertainty about whether this venture will succeed or fail is very high.

So, rather than put together detailed plans about building the product that the business will be based upon, a startup venture should be building the “minimum viable product” and getting feedback from customers quickly to see whether you’re on the right track.  The faster you get feedback, the better you’ll be able to build a business that is sustainable and meets the needs of your customers.

Effectively, Ries argues that you should treat the startup venture, every aspect of it, as a series of scientific experiments designed to inform you whether you are building a sustainable business consistent with your company’s vision.  It’s basically applying the scientific method to your business.

For one, I say, “Absolutely dead on!”  Most business activities, whether marketing or sales or even less-than-disciplined engineering, are performed via rules of thumb (“here’s what’s worked before…”) - there is no true “validated learning”, as Ries put it.   Generally, many businesses and engineering teams operate with the approach of “we made a number of changes last month, and our customers seem to like them, and our overall numbers are higher this month, so we must be on the right track”.  This might make a company feel good, but it gets them no closer to understanding why they might be succeeding, and what to do if things turn south.

And what is worse, the internal workings of the business may be driven by managers more motivated by preserving the current business enterprise than creating a new one.  This puts entrepreneurial ventures at risk from getting started in the first place, or at least started with the greatest possible chance for success.

And I like the way that Samild describes it in his post:

In the twenty-first century we can build almost anything that can be imagined. The challenge is not to build more stuff. It’s to build the right stuff. Most startups fail, says Ries, because they make the wrong things. The key activity of a startup should therefore be learning, not building. What creates value for a startup is it determining whether or not it’s on the path to a sustainable business.

If you’re interested in the Lean Startup approach to business (which, again, I highly recommend), you can find out more at Eric Ries’ website here, and you can buy his book The Lean Startup here…  Also, you can read more of Stephen Samild’s post here…

Shvetank Shah is executive director of the Corporate Executive Board, and recently wrote an article for InformationWeek about the need for scrutiny when launching into big data initiatives.  Here’s the first paragraph from Shah’s post, which sums things up pretty well:

Even as companies invest eight- and nine-figure sums to analyze the information streaming in from suppliers and customers, fewer than 40% of employees have the right processes and skills to make good use of the analysis. Think of this as a company’s insight deficit. To overcome it, “big data” needs to be complemented by “big judgment.”

Just because we now have lots of data to work with doesn’t mean that we will now get better decisions.  How we turn data into actional information – the methods, the tools, the techniques – are incredibly important.  Also, as Shah points out, sometimes the data itself is just plain bad, and people don’t always trust it.  Gaining insight from data is the important factor, not merely getting more data.

You can read Shah’s post on InformationWeek here, and more from CEB on this topic is available at insightdeficit.com.