FinancePBI Begins its Shakeout Flight in the Cloud
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.
In the meantime, the product now in beta is being kicked around by a bunch of folks in the Financial Services community. Its ease of use, customizability, performance, and ability to do streaming analytics on user defined metrics in real-time on both intrinsic data (Tick feeds) and user uploaded data using standard technology and cloud infrastructures is blowing people away.
As a company that has been focused on big analytics for quite a while (starting out in that other big analytics industry retail ), it’s been gratifying to watch customers and the analyst community move beyond focusing on how fast data can be stored or how fast you can do a word count with Hadoop. Instead, the focus has shifted (finally!) to how you can create an analytics system that:
- Supports large streaming data sets (like twitter and tick data).
- Is maintainable, easy to use, and doesn’t require a permanent army of “forward deployed engineers.”
- Is accessible and useable to everyone in your business from quants to analysts.
Admittedly, I was one of the folks that helped push the term big data. But in reality, any data that you can’t analyze effectively is big data and given how hard it is to do any type of real analysis with traditional BI tools or multi process frameworks disguised as analytics systems like Hadoop, it’s pretty clear that we are at the beginning of the big analytics journey (not the end).
In my next blog, I am going to talk about the various integration points in FinancePBI and how the release of products, like CloudNumerics for Azure and DynamoDB from Amazon, are going to make this the year of cloud analytics in lots of industries and how we and our partners are planning to lead that charge in the financial services industry.