A method for managing network event data in a telecommunication network, wherein the network event data is associated with products provided by different vendors, the method comprising: obtaining a plurality of datasets, wherein each dataset comprises network event data associated with products provided by a single vendor, and wherein each dataset comprises a plurality of data instances representing a plurality of network event features; obtaining metadata describing the network event data in the datasets; for individual network event features represented in the datasets, generating a feature description vector from the obtained metadata; calculating, on the basis of the generated feature description vectors, a metric of the relation between network event features represented in the datasets; constructing a graph of the network event features represented in the datasets, wherein edges between the network event features are weighted according to the calculated metric; partitioning the graph into clusters by minimising an edge cut between network event features; for individual clusters in the graph, labelling network event features in the cluster with a normalised network event feature index, which index is unique to the cluster and corresponds to a specific normalised network event feature; and inputting the network event data representing the labelled network event features to a model for making at least one of recommendations or predictions based on input data representing normalised network event features, wherein the calculating comprises computing a pairwise similarity between the feature description vectors of the network event features represented in the datasets. obtaining a plurality of datasets, wherein each dataset comprises network event data associated with products provided by a single vendor, and wherein each dataset comprises a plurality of data instances representing a plurality of network event features; obtaining metadata describing the network event data in the datasets; for individual network event features represented in the datasets, generating a feature description vector from the obtained metadata; calculating, on the basis of the generated feature description vectors, a metric of the relation between network event features represented in the datasets; constructing a graph of the network event features represented in the datasets, wherein edges between the network event features are weighted according to the calculated metric; partitioning the graph into clusters by minimising an edge cut between network event features; for individual clusters in the graph, labelling network event features in the cluster with a normalised network event feature index, which index is unique to the cluster and corresponds to a specific normalised network event feature; and inputting the network event data representing the labelled network event features to a model for making at least one of recommendations or predictions based on input data representing normalised network event features, wherein the calculating comprises computing a pairwise similarity between the feature description vectors of the network event features represented in the datasets.