Supply Chain Global Lakehouse

For one of the leading multinational automotive manufacturing company, formed on merger of two of the most important automotive companies, Technology Reply designed and implemented a solution of convergence, in a Data Platform domain, to collect information through a single point in a timely and flexible way.


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:

  • The modeling and the development of structures containing data related to the design of routes in logistics stations, with the aim of verifying whether delays could occur within the identified milestones and, if so, identifying possible corrective actions
  • The analysis and the development of specific KPIs in order to provide detailed reporting, daily and/or monthly, related to budget trends, sales and vehicle inventory

A cloud technology data platform

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.

  • A Software as a Service (SAS) on a cloud platform, allows the access to the multiple instances, optimizing performance and speed access. One of the main features of the data platform is the ability to access the content of regional databases (each one dedicated to the individual region) leveraging replication mechanisms through a single query – across all the regions. The content of the databases is then transformed and moved to global and harmonized instances , dedicated to specific business areas
  • A custom Framework, designed not only to orchestrate complex processes, but also to define a metadata-driven process and automatically perform congruence and quality checks on the data before next steps to the Target layer
  • A cloud-based ETL service, used to design and manage the pipelines and to automate data collection and transformation process, starting from a lower layer, containing raw data - regionals data, to the upper Business Layer, containing processed data in order to facilitate the analysis of the desired business process


The Technology Reply team dealt with several challenges:

  • Unifying information from different companies, in order to harmonize data belonging to different data structures, languages and integration methodologies
  • Analysis and definition of data modeling with the contribution from different stakeholders with different perspectives (business users, regional ICT)
  • Management and collaboration among teams in co-design approach, between Technology Data engineer teams and the client
  • The definition of guidelines and shared best practices to organize data from a regional view to a standardized business level
  • Harmonization and convergence techniques to ensure a common business repository


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.