From the consolidation of a 20-years collaboration with a company among the leading Italian car manufacturers, Technology Reply had the opportunity to increase their technical and functional skills to the international ground.
After the joint venture, the main goal was the necessity to collect data from regions worldwide, in a single global database, allowing business users to access to integrated reporting system in the Supply Chain environment.
We had the opportunity to setup this collaboration after the corporate merger context, the most delicate of the entire process, requiring changes in organizational assets, structures and new interactions between stakeholders.
The design of the Global Lakehouse began with the creation of a Data Platform dedicated to the Supply Chain department, to reach the goal of unearth the entire logistical life cycle of the car, from the issue of purchase order to the delivery of the product to the final customer. The main purpose was the design of a solution to perform business analysis on a series of key KPIs of interest.
The project was divided into two main waves:
In order to meet client's requirements, Technology Reply developed a data platform entirely based on cloud technology, structuring the data collection process into different phases: a Standard Pipeline allows to define the integration process, from regional raw data to a high level of data preparation, according to the best practices of business analytics processes and leveraging Snowflake capabilities.
Data quality checks, entity data lineage and orchestration of complex processes have been enabled by a custom metadata-based framework. An asset layer manages a data global view with a homogeneous data model that enables analytics both at the regional and business level, in order to achieve optimized front-end analysis.
The Technology Reply team dealt with several challenges:
The solution developed by Technology Reply for the Supply Chain project paved the way to the modus operandi adopted by our client, not only in terms of data convergence and harmonization rules on the new architecture, but also in terms of the methodology to adopt for the next projects: a co-design approach was adopted for the development activities, helping the Data engineers team of our customer to design new solutions in the Data Platform area.