June 20, 2011
Today I’m blogging from Enzee Universe, Netezza’s seventh annual user conference, and want to share the latest news from the show.
June 19, 2011
This week at the IBM Netezza Enzee Universe show in Boston, we’re taking the covers off IBM’s strategy for data warehousing and analytics and we’ll be talking about what that’s going to mean for the joint product portfolio.
June 14, 2011
Many analysts have a strong preference for commercial analytic workbenches such as SAS or SPSS. Both packages are widely used, respected by analysts, and each has strong advocates. The purpose of this article is to point out that analytic users can benefit from the performance and simplicity of Netezza in-database analytics without abandoning their preferred interface.
June 8, 2011
With Enzee Universe fast approaching we are in the last days of the I.D.E.A. Challenge, open to all registered members of the Enzee Community. New members can register here.
June 2, 2011
There is a huge diversity of data generating sources today, the Internet, sensors, operational systems, field systems, shop floor systems, etc. All this data enters into a pipeline of data flowing into corporations that can clog up even the most sophisticated of companies. Do we need it all? Is it useful? Is all of this big data equally important? Let’s take a look at where the data comes from and how it can be used over time.
May 31, 2011
Who are the users for analytic solutions? In developing solutions, we tend to think of one group of users, those who work with statistical packages like SAS or SPSS. In reality, every analytical solution has three distinct user communities whose needs must be addressed.
May 19, 2011
All companies, big or small, are looking to improve their sales while reducing their operating costs. Be it reliable customer segmentation and targeting, accurate forecasting, improved inventory control, or higher-quality manufacturing processes, analytics have long been seen as the key to this goal: Business Optimization. Just as analytics have been around for a long time, our approach to developing analytics and leveraging them into a business has been around a long time as well.
May 12, 2011
Enterprises seeking to increase the volume and scale of deployed analytics frequently run into what we call the model migration bottleneck -- that's where analytical models developed offline in a statistical package must be deployed into a scalable IT-managed production environment. Customers and software vendors have tried numerous approaches to managing this constraint, but for many firms the solution is to physically recode and test the model -- a process that can take weeks or even months. When analytics are a key competitive tool and speed is of the essence that is not an acceptable approach. Clients sometimes ask is of PMML is a solution. PMML, or Predictive Model Markup Language is a standard published by the Data Mining Group, an independent consortium of leading analytical software vendors, service providers, analytics consumers and thought leaders. An XML-based standard, PMML has evolved progressively since first released in 1997, and is currently in Version 4.0.
May 10, 2011
All too often, the morning news brings us a headline about another potentially catastrophic failure in a manufacturing part or process, such as the recent mid-flight airliner fuselage crack or tire failures associated with vehicle rollovers. Certainly, manufacturers have many processes in place to detect and resolve defects, particularly those that might endanger the public. While statistics and other analytical techniques are part of those processes to understand the root causes of defects, in many cases such analysis is done outside the operational environment and thus may take some time for findings to be translated into corrective actions.
May 3, 2011
CMOs today are inundated with massive quantities of data from external data providers and internal systems. Yet the still strive to find elusive answers to these questions: What new product can we introduce that will address new highly profitable emerging markets we’d like to enter? If we make this competitive maneuver, what are the most likely moves our competitors will make and how will that impact the entire market? The economy is collapsing in our highest profit region, what are the best actions to take now to backfill for that profit? What are the right messages to convey in our advertising that will positively impact the customer experience? How can we maximize our overall marketing budget and resources while simultaneously increasing revenue growth and customer loyalty? What are the right social networks to tap into to leverage and extend our reach?