Certain example embodiments relate to using Complex Event Processing (CEP) techniques for statistical analysis of cache behavior and parameters, e.g., in connection with large, potentially heterogeneous data sets (e.g., “Big Data”). A dedicated stream mining operator registers a listener to a cache and receives notifications on cache operations. For selected element attributes, a first model estimates the probability density functions of the attribute values, delivering well-defined estimates of the attribute value distributions. A second model analyzes the time elements stay in the cache (“validity”). Validity is combined with the attribute value distribution. A meaningful analysis model (Cache Element Model) can be derived by combining additional summary statistics for the validity with the attribute value distribution, describing how long elements stay in the cache for attribute values of a specific region, and how the values are distributed. It may be used to inform administrative tasks such as, optimization of cache parameters.