Diving Deep into Analytics from the Netezza Platform - Part Deux
In theory there is no difference between theory and practice. In practice there is.
-- Jan van de Snepscheut, 1953-1994, computer scientist and educator, California Institute of Technology
So, yesterday I wrote about "the Netezza's" transformation into a platform for deep analytics. Now I know a platform is only as good as the applications available on it, which brings me to our announcement this morning.
Last September, we got together with a handful of visionary partners and customers and created the Netezza Developer Network (NDN) with the goal of developing truly innovative analytic applications. We announced the first wave of these offerings today, with 5 NDN partners delivering game-changing applications built using Netezza's OnStream analytics. Let me highlight a couple of them here.
Systech Solutions' profitability analysis application for retail and CPG companies provides cost and revenue analysis at the detailed SKU and customer level. It gives business users the ability to build and run profitability models using a GUI, instead of relying on IT to do it for them. This is pretty unique, because traditionally something like this would take huge amounts of time - measured in many months - not to mention the resources required. Their app cuts this down by orders of magnitude! So you not only get very fine-grained profitability analysis, but it's available very, very quickly. That makes all the difference between gut-feel decisions and data-based ones about which products and customer to keep, which prices to re-negotiate and how to truly impact the bottom line.
Imagine if telco service providers could analyze each and every one of the many millions of call detail records they collect and store, before making very important decisions - the kinds that can dramatically alter their earnings statements. That's what RateIntegration's app offers - a tool for business users that allows them to model the impact of competitors' pricing and regulatory changes to figure out the most optimal rate plans. Business analysts can also directly implement custom scoring algorithms for customer segmentation and profiling using their flexible rules engine.
Apart from these, we have Multi-Threaded Inc's fuzzy name and text matching app for critical anti-terrorism, money laundering and digital forensics operations; HCL Technology's implementation of Monte Carlo simulations for pricing derivatives; and Edge Associate's library of SQL functions to speed up migrations to "the Netezza". Make sure you check out the brand spanking new applications webpage to get more details about each of these members and their applications, and don't forget to stop by their booths at the User Conference.
"As long as one does not have to wait minutes to hours between computational gestures, something amazing happens; one gets problem solving at the speed of human insight"
-- Data-Centric Computing with the Netezza Architecture, Sandia National Laboratories
While the new applications developed by NDN members are unique and serve very different markets - retail, telecommunications, financial services and government - they have remarkable similarities in the value they offer to customers. The applications power complex analytics orders of magnitude faster than economically feasible before, allowing users to perform "what-if" analyses to more accurately predict future outcomes. These analyses can be performed on large volumes of detailed data, providing unique business insights that would otherwise be lost in sampled and summarized data. The deployment and management of the overall solution is greatly simplified, freeing up business users to focus on results rather than worrying about tuning and maintaining the system.
What's really neat about Netezza's open platform approach is the ideas and innovation it is generating and the differentiated applications it is helping launch. Now that's what platform innovation is all about, isn't it? At Netezza, it's about bringing the power of analytics to the mainstream.