A long-established industrial company specializing in the design and production of high-tech components for braking, transmission, and cooling systems has embarked on an innovation journey to enhance internal efficiency and service quality. Operating globally with production plants across multiple continents, the company has always prioritized quality, safety, and technological advancement.
Faced with continuous expansion and increasing operational complexity, the need arose to automate internal processes responsible for generating and managing reports, which until then had been handled manually. The objective was to reduce turnaround times, eliminate repetitive activities, and improve the accuracy of daily data analysis.
Objectives
The project focused on building a data warehouse within Google Cloud Platform, capable of centralizing and managing structured data from SAP and other systems. On top of this infrastructure, the goal was to create a daily, automated ETL reporting pipeline using Data Studio to support business decisions with up-to-date data.
To meet these needs, we developed a Python-based framework hosted on a dedicated VM capable of orchestrating end-to-end pipelines for data collection, transformation, and loading. The process was rolled out in several phases:
Automated download of SAP files and company system datasets, saved in Google Cloud Storage
Data transformation (standardizing columns, cleaning, adding load timestamps)
Loading into a BigQuery staging dataset
Activation of a BigQuery stored procedure for further transformations and ingestion into the final dataset
All operations were orchestrated via daily scheduled cron jobs to ensure complete automation based on a regular cadence.
The Results
The project delivered significant benefits in terms of operational efficiency and scalability. The company gained a cloud-native platform with high computational capacity, surpassing the limits of previously used proprietary systems. The entire data pipeline—from extraction, transformation, and loading—has been fully automated, eliminating manual tasks and reducing error margins. The capability to generate daily up-to-date reports improved the quality of analysis and supported decision-making in a more effective and timely manner.
Key Benefits
Scalable resources and greater processing power
Automated access to SAP-derived data
Fully automated ETL pipeline
Centralized, always up-to-date data warehouse
Elimination of manual tasks and increased internal efficiency