Scenario
Technology Reply responds to the need of large multinationals specialized in fashion to have a centralized database that allows the use of all the data coming from the various information systems. This database is the Enterprise Data Warehouse, Enterprise because it has to manage the information assets of all the brands that make up the group's portfolio, managing their peculiarities but also facilitating the transfer of knowledge and calculation rules between one brand and another.
Through Data Integration processes, data are acquired from heterogeneous sources, validated, integrated and made available through coherent and well-organized data structures. The data thus validated and structured are used for the construction of specific Datamarts that collect metrics and KPIs, even very complex ones.
The Data Integration and the feeding of the various Datamarts take place through structured ETL/ELT processes governed by a process management framework developed with the aim of standardizing the development of flows, reducing the effort for the acquisition of new information, ensuring the correct loading of data and that in case of anomalies, through notification alerts, allows a better management of any problems.
Information management is focused in order to meet all the needs of the typical processes of companies operating in this sector, covering the entire supply chain: from the procurement of raw materials, warehouse and production movements (supply chain), through orders of the finished product (sell-in), financial analysis (active and passive cycle), up to the purchase of the final consumer (sell-out & CRM). Particular attention was paid to the definition and calculation of "Customer KPIs", metrics that aim to analyse customer behaviour so as to be able to implement effective and personalized responses for each customer segment (eg targeted promotional campaigns).
The data of the Enterprise Data Warehouse are then used as a single source of truth for the construction of institutional dashboards, to perform Data Analysis, as input to other processes / information systems or for Data Discovery or Data Science processes.