With the increasing amount of available data and transformations manipulating the data, it has become essential to analyze and debug data transformations. A sub-problem of data transformation analysis is to understand why some data are not part of the result of a relational query. One possibility to explain the lack of data in a query result is to identify where in the query we lost data pertinent to the expected outcome. A first approach to this so called why-not provenance has been recently proposed, but we show that this first approach has some shortcomings. To overcome these shortcomings, we propose \ned, an algorithm to explain data missing from a query result. NedExplain computes the why-not provenance for monotone relational queries with aggregation. After providing necessary definitions, this paper contributes a detailed description of the algorithm. A comparative evaluation shows that it is both more efficient and effective than the state-of-the-art approach.