Spreadsheets are widely used for statistical analysis; and while they are incredibly useful tools, they are useful only to a certain point. When used for a task they're not designed to perform, or for a task at or beyond the limit of their capabilities, spreadsheets can actually be dangerous. This paper presents some points you should consider if you use, or plan to use, a spreadsheet to perform statistical analysis. It also describes an alternative that in many cases will be more suitable.

Businesses today have more raw information than ever before. But many lack the analytics to make good use of it. Read this report from Ventana Research for practical recommendations on how to implement business analytics to improve performance.

While many large enterprises have adopted analytics technologies such as business intelligence (BI), performance management (PM), and predictive analytics, misperceptions about costs and risk have caused small and midsize companies to embrace these technologies far more slowly. See how investing in analytics tools can improve operating results by enabling managers to make decisions that are more fact based and data driven.

Large enterprises have long had access to Business Intelligence (BI) in various forms – analytics software integrated with accounting, process automation, sales force management, and other systems, that provide reporting to stakeholders appropriate to each function. Until recently, BI solutions for the midmarket were stymied by economics: enterprise solutions were too cost-intensive and required too much lengthy and difficult integration with companion systems and data-sources. Worse, as use of these systems evolved, it often turned out that valuable IT resources were required to maintain BI systems and their integrations, and create a myriad of custom reports needed by all the key stakeholders.