What kind of analysis does OLAP enable in RelativityOne?

OLAP, or Online Analytical Processing, is designed specifically to perform multidimensional analysis of business data. In the context of RelativityOne, it allows users to analyze and interact with data in various dimensions, such as time, geography, and other categorical dimensions. This capability enables users to quickly retrieve and organize data into meaningful structures for reporting and decision-making.

Multidimensional analysis helps in evaluating complex data relationships, providing insights that are not readily apparent in flat data structures. For instance, users can slice and dice data across different hierarchies and dimensions, gaining a richer and more nuanced understanding of their datasets. This is particularly useful in legal and investigative contexts where data can be extensive and complex.

While qualitative analysis focuses on descriptive data and insights drawn from observations or interviews, and quantitative analysis emphasizes numerical data and statistics, OLAP's strength lies in its ability to aggregate and analyze data across multiple dimensions simultaneously. Predictive analysis, on the other hand, involves using statistical techniques and algorithms to forecast future outcomes based on current and historical data, which is not the primary function of OLAP in this context. Therefore, multidimensional analysis is the most accurate description of what OLAP enables in RelativityOne.