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Unifarm

DataExpress is a web BI dashboard system developed for Unifarm S.p.a., a consortium of about 700 pharmacies providing services as stocking, distribution logistics, commercial support and promotional actions. Unifarm collects the sell-in/out data coming from different pharmacy's ERP softwares, thus generating a harmonized data stream.

We have endowed DataExpress with a set of statistical machine learning tools typical of high throughput bioinformatics, e.g., clustering procedures for time-series. Machine learning functionalities are actionable from on-line graphs, such as biclustering panels in which subset of pharmacies and sales categories can be interactively selected. Currently 210 million entries are managed from the sales stream within the system. Network analysis (detection of community structure and co-occurrence patterns) combined with geospatial and socio-economic data are being developed as strategic tools.

DataExpress is implemented as a web-based Django framework deployed on a AWS machine, using Celery and Redis to distribute tasks. This scalable framework can be accessed through a web interface from the strategic marketing and R&D departments and other directive figures; a similar and leaner interface is available for the individual pharmacy owners. The DataExpress web interface integrates Javascript libraries to obtain interactive displays connecting machine learning and data exploration (D3js, Highcharts, Sigma.js, Heatmap.js, leaflet, InCHlib). Actionable dendrogram structures and sunburst plots allow the handling of big taxonomies typical of the pharmaceutical reference structures. Internally, the statistical machine learning methods are deployed as stored procedures for a PostgreSQL/PostGIS database, powered by the PL/R extension.