The Analytics area is covered by two components, GrimoireELK and Cereslib. The first one implements the core GrimoireLab pipeline: obtaining JSON items from the Data Retrieval components, storing them with persistence in "raw indexes", enriching those indexes by producing items more suitable for visualization and reporting, and storing them in persistent "enriched indexes". In the process, GrimoireELK also uses SortingHat, in the Identities Management area, for identifying new identities, and finding the corresponding unique (merged) identities. Since both raw and enriched indexes are Elasticsearch indexes, they are basically collections of JSON items (named "documents" in Elasticsearch). All usual operations on noSQL databases are possible on those indexes: retrieving one or more items given some constraints, aggregating values for certain fields for a certain selection of items, updating items matching certain values, etc. The other component, Cereslib, is a library providing an API with useful functionality for certain kinds of specialized functionality. The Cereslib API is invoked by GrimoireELK to run "studies", which produces some specific enriched indexes. Studies are specialized preanalysis, producing items with a specific aim in mind. For example, one of them, "Areas of code", produces commit **data** at the file level (each item consists of commit metadata for each revision of each file), which is useful to analyze how different areas of code evolve.