Posts tagged ‘Cloud’
I apologize for falling behind on blogging, but between several new hires, major partnerships, and the industry finally starting to understand the need for product-driven (instead of project-driven) big data, things have been very hectic. Good, but hectic.
I did want to pull my head off my keyboard for a minute to tell you about participating in the big data & real estate panel this Thursday at Connect San Francisco. Our panel will be moderated by industry luminary Brad Inman @bradInman.
Real estate has always been a data-driven business and is relying more and more on the insights and operational nimbleness provided by big data. For those of you who are scratching your heads and going, “Huh, Real Estate and big data?” – think about it for a minute. The real estate industry is “using” big data to do all kinds of things and drive all kinds of business models, such as:
- Commercial landlords using smart thermostats and smart windows adjusted in real-time to save energy.
- Capturing real-time parking meter data to make real-time decisions about how long to leave a retail location open.
- Using real-time video analysis to stop vandalism before it happens.
- Offering sophisticated analytics – see consumer facing sites like Truila and Zillow.
- Risk Modeling – check out RMS. Like most of the PatternBuilders team, they were “doing” Big Data before the term was invented.
If you are attending the show, stop by and say hi. If you are interested in Big Data & Real Estate, look for our post-Connect blog next week. In it, we will talk about some great insights about the New York real estate market derived from a ton of data we grabbed from the NYC public data market which was then spun up in the PatternBuilders framework on our brand spanking new Microsoft Azure cloud beta release.
I have been a little quiet on the blogging front recently as I and the rest of the PatternBuilders team have been focused on getting ready to launch our new financial services application: FinancePBI. It is the first cloud-based analytical platform for the Financial Services market. While this is our first public announcement of our entry into the market, behind the scenes we have been gearing the company up for a big splash for several months:
- Partnered with ActiveFinancial one of the premier real-time stock ticker vendors in the world. Look for more data partnerships shortly.
- We have added Doug Jeffrey to our board of advisors and board of directors. Doug is an executive with deep Wall Street and startup expertise who has already done outstanding things in the short time he has been with us.
- We have also partnered with the University of Sydney to use our technology to examine the influence of primary sources (NY Times, etc.) and secondary social media (Twitter, etc.) content on a company’s stock price over a 12 month period. This project will be done exclusively in the cloud and it’s our hope is that we will be able to convince our commercial partners to allow this PatternBuilders instance to be available to the general public. Of course, this would happen after the research is published. (more…)
All you need is text, Text is all you need (sing to the tune of The Beatles’ All you need is love). If you are one of our regular readers you will remember that several months ago I wrote a manifesto on what the perfect analytics system would look like. One of the last points was:
It must be as accessible as Excel (still the number one analytics tool in the world).
I was wrong – Excel is the number one non-specialized analytics tool in the world but in terms of usage, it is dwarfed in comparison to a very well know specialized analytics toolkit. The creators of this tool are a little company that you may have heard of: it does no evil and analyzes the Internet to bring you back everything on the web based on a simple text query. But behind that simple text box, Google has one of the most sophisticated analytics infrastructures in the world:
- It can deduce your interests.
- Give you the most relevant results.
- And show you appropriate information based on them, as well as bring back highly personalized ads.
Google is not only the largest big data analytics company in the world, but it also has the easiest to use tools—proof that text is all you really need!
As you all know, Tim and I spoke at MongoSF recently. Our session was focused on how to build a streaming analytics system with Mongo. For those of you who might have missed this post thread, here are the highlights (with the appropriate links):
- We wanted to make our beta version of PatternBuilders Social Media Analytics demo publicly available on the web.
- We looked at cloud-based deployments as a way to make this economically viable.
- As part of our move to the cloud, we made significant changes to PatternBuilders Platform architecture—which included MongoDB (a choice that the PatternBuilders development team is very happy with).
Our session was videotaped and I am happy to announce that it is now available on the 10gen site. You’ll notice that we got a lot of great questions. If, after viewing the video, you have some thoughts or questions please send them my way through comments or email—it may take me some time (we are, as Mary said in her last post, crazy busy right now), but I will follow up!
When we started PatternBuilders, we made what was then an unusual decision: to avoid multi-tenancy as I talked about here. However, we also decided to avoid the cloud because we wanted to have predictable costs and felt that given the high level of expertise we had internally with managing data centers, we would be better off investing in top tier colocation facilities. This made a lot sense given the security sensitivities of our initial target markets: internal IT at the Fortune 500, large retail suppliers, and hospital groups. It was also an economically viable choice because our business model provisions hardware and bandwidth for each customer after the sale to manage cash flow. We also knew that we would be able to reduce both the cost and maintenance headaches of separate customer provisioning by aggressive use of virtualization technology, much like the cloud server vendors Rackspace, Amazon, and others do today.
In my last post, I talked about how the time sharing model for enterprise apps was displaced by user owned data centers and on premise deployments of enterprise software. In the late nineties, a plethora of companies tried to reinvigorate the timeshare model, using the Internet as a cheaper network backbone.
These companies, collectively called Application Service Providers (ASP), used a variety of different approaches to deliver enterprise software over the web. They ranged from: (more…)