SPSS, a leading worldwide provider of predictive analytics software, today unveiled one of the most robust releases of its enterprise data mining software, Clementine 11.0.
The evolution of this product features dramatically enhanced solutions through the addition of data analytic techniques and innovative graphic capabilities.
Version 11.0 of Clementine enables organisations to enhance productivity in customer relationship management (CRM), marketing and risk analysis, and provide analysis for fraud detection. This product is a key component of the company's market-leading predictive analytics offerings. Additionally, this release is now tightly integrated with the SPSS statistical products, giving users easy access to statistical and data management capabilities.
Colin Shearer, senior vice-president of market strategy at SPSS, led the team that designed and developed Clementine in the early 1990s. "Clementine has led the data mining market for more than a decade, particularly among organisations looking to boost their CRM return on investment," Shearer said.
"The innovations in Clementine 11.0 push it even further ahead, taking SPSS' predictive platform to a new level by providing unequalled support for analytical productivity and bridging the gap between advanced analytics and business solutions."
Atique Shah, vice-president of direct marketing and consumer insights at EarthLink, an Internet service provider and SPSS customer, said, "We are extremely impressed with the customer-centric response from SPSS in advancing their data mining product to help organisations, such as EarthLink, better meet their customer marketing needs."
Tilmann Bruckhaus, director of analytics at Numetrics Management Systems, the leading provider of project planning tools to the semiconductor industry, added, "Clementine 11.0 considerably expands the product with attributes that will drive the use of analytics deeper into an organisation and broaden its use in any business. As a product beta tester, I'm extremely excited about the significant advancements to this version that bring Clementine above and beyond prior releases."
In commenting on the new product developments, Anthony Colyandro, data analyst/data management at government consulting firm SRA International, said, "SPSS is on the cutting edge of predictive analytics technology, and Clementine 11.0 offers new capabilities that will enable us to provide the best business solutions to our clients."
First released in 1994, Clementine is SPSS' industry-leading data mining workbench. Clementine customers span across many industries - including finance, banking and insurance, telecommunications, retail, utilities and pharmaceuticals - and total several thousand users.
SPSS was positioned in the Leaders Quadrant of key industry analyst firm Gartner Inc.'s Magic Quadrant. In the report, Gartner stated leaders are performing well today, have a clear vision of market direction and are actively building competencies to sustain their leadership position in the market.
Gareth Herschel, research director at Gartner, said in a recent presentation, "There is an ongoing explosion in the volume and variety of data available within organisations." He also noted, "data mining is an important form of analysis for companies from a variety of industries to understand."
More Specific Benefits of SPSS' Clementine 11.0:
New algorithms empower new application areas
Increased analytical power and functionality have been introduced with specific business solutions in mind. New algorithms provide support for credit scoring (discriminant function analysis), complex pricing models (generalised linear models), CRM and response modeling (logistic regression), forecasting (time series) and rule-based models that incorporate users' business knowledge.
Productivity improvements increase efficiency
The time to develop and deploy models has been significantly reduced due to the development of more robust transformation capabilities, more automated data cleansing and the use of optimal binning to enable more predictive power. Developing and selecting the best model is made simple by building multiple models simultaneously with the binary classifier.
Better graphical output and improved management communication and insight
Customers are now able to easily edit and distribute presentation-quality images, providing more efficient management reporting and more effective communication through a powerful new graphics engine and integration with the reporting and high-quality graphics of the SPSS statistical products.
Integration contributes to better performance and greater leverage of existing investments
Clients can now fully leverage their IT investments by using the parallelism in high-performance hardware and software (such as multiprocessor or multicore systems), as well as data mining algorithms provided as part of the database systems by IBM, Microsoft and Oracle. The use of secure sockets layer (SSL) encryption and stream password protection of files heightens the security of sensitive data.