Data is one of the most valued assets within an organization. The amount of data that is being generated and kept for availability and analysis by organizations is exploding.

The telecommunications industry is characterized by intense competition and customer attrition, or “churn.” Targeted marketing opportunities and the rapid response to behavior trends are paramount to the success of telecommunications service providers in retaining existing customers and attracting new customers. Customer relationship management, or CRM, analyses need to be constantly and quickly performed, to enable service providers to market to at-risk customers before they churn, offer new products and services to those most likely to buy, and identify and manage key customer relationships.

For online businesses, the process of collecting, analyzing and reporting data about page visits, otherwise known as click stream analysis, is required for constant monitoring of website performance and customer pattern changes. In addition to needing to address the operational and customer relationship challenges faced by traditional retailers, e-businesses must also analyze hundreds of millions or even billions of click stream data records to track and respond to customer behavior patterns in real time.

The significant growth of enterprise data is fueling a need for additional storage and other information technology infrastructure to maintain and manage it. According to a 2006 report by IDC, an independent technology research organization, worldwide shipment of disk storage systems capacity exceeded 2 million terabytes in 2005 and is forecasted to grow to over 16 million terabytes in 2010, representing a compound annual growth rate of approximately 51%. This growth in data is being further fueled by a steady decline in data storage prices, which makes storing large data sets more economical.

As the volume of data continues to grow, enterprises have recognized the value in analyzing such data to significantly improve their operations and competitive position. They have also realized that frequent analysis of data at a more detailed level is more meaningful than periodic analysis of sampled data. These factors have driven the demand for the data warehouses that provide the critical framework for data-driven enterprise decision-making by way of business intelligence.

The Company designed its NPS data warehouse appliance specifically for analysis of terabytes of data at higher performance levels and at a lower total cost of ownership with greater ease of use than can be achieved via traditional data warehouse systems. The Company’s NPS appliance performs faster, deeper and more iterative analyses on larger amounts of detailed data.

The 10000 Series is the Company’s core performance line, with current data capacity ranging from less than one terabyte of data up to 100 terabytes. This is the primary product line from which the Company derives the substantial majority of its revenue. The 10000 Series currently consists of six product models (10050, 10100, 10200, 10400, 10600 and 10800).

The 5000 Series, which currently consists of one product model, has available data capacity of up to three terabytes, with prices ranging from less than $200,000 to $250,000. This product is sized and priced for the Company’s mid-market and smaller customers and does not need to be deployed in a data center, which offers more flexibility to these customers.

Sales and marketing expenses increased $7.3 million, or 28%, to $32.9 million in fiscal year ended January 31, 2007 from $25.6 million in fiscal year ended January 31, 2006.

Research and development expenses increased $1.3 million, or 8%, to $18.0 million in fiscal year ended January 31, 2007 from $16.7 million in fiscal year ended January 31, 2006.

The Company incurred $0.4 million of interest expense, net in fiscal year ended January 31, 2007 as compared to $0.3 million of interest income, net in fiscal year ended January 31, 2006.