Analytics engine selection management

Abstract

Disclosed aspects relate to analytics engine selection management. A set of reference data may be ingested by a first analytics engine to compile a first set of characteristic data. The set of reference data may be ingested by a second analytics engine to compile a second set of characteristic data. The first set of characteristic data may be compiled for the first analytics engine. The second set of characteristic data may be compiled for the second analytics engine. A set of distinct attributes related to the first and second analytics engines may be determined based on the first and second sets of characteristic data. An analytics engine selection operation may be executed.

What is claimed is: 
     
         1 . A computer-implemented method for analytics engine selection management, the method comprising:
 ingesting, by a first analytics engine, a set of reference data to compile a first set of characteristic data for the first analytics engine with respect to the set of reference data;   ingesting, by a second analytics engine, the set of reference data to compile a second set of characteristic data for the second analytics engine with respect to the set of reference data;   compiling, with respect to the set of reference data, the first set of characteristic data for the first analytics engine;   compiling, with respect to the set of reference data, the second set of characteristic data for the second analytics engine;   determining, based on the first and second sets of characteristic data for the first and second analytics engines, a set of distinct attributes related to the first and second analytics engines;   resolving, to determine the set of distinct attributes related to the first and second analytics engines, a set of computing cost data for the first and second analytics engines;   resolving, to determine the set of distinct attributes related to the first and second analytics engines, a set of resource usage data for the first and second analytics engines;   resolving, to determine the set of distinct attributes related to the first and second analytics engines, a set of precision-indicative data for the first and second analytics engines;   resolving, to determine the set of distinct attributes related to the first and second analytics engines, a set of recall-indicative data for the first and second analytics engines;   resolving, to determine the set of distinct attributes related to the first and second analytics engines, a set of typological data for the first and second analytics engines;   resolving, to determine the set of distinct attributes related to the first and second analytics engines, a set of error-event data for the first and second analytics engines;   executing, using the set of distinct attributes related to the first and second analytics engines, an analytics engine selection operation;   arranging, the set of candidate analytics engines based on a corpus topic distribution property, a corpus writing level property, a corpus dataset size property, and an analytic effects property;   selecting, to execute the analytics engine selection operation using an analytics engine selection criterion which corresponds to the set of distinct attributes related to the first and second analytics engines, an appropriate analytics engine; and   processing, using the appropriate analytics engine, a set of content data to generate a valid results-set.