Even the most common descriptive statistics calculations can become complicated when you are dealing with big data. You donít want to be restricted by column limits, storage constraints and the limited data type support of traditional data architectures. The answer is an in-memory engine that accelerates the tasks of data exploration and a graphical interface that displays the results in simple visualizations.
Large numbers of users, including those with limited analytical and technical skills, can quickly view and interact with reports via the Web or mobile devices, while IT maintains control of the underlying data and security.
The net effect is the ability to accelerate the analytics life cycle and to perform the process more often, with more data Ė all the data, if thatís what best serves the purpose. By using all data that is available, users can look at more options, make more precise decisions and succeed even faster than before.