Vasco Electronics is a technology company operating in multiple markets that uses data as a key element of reporting and business decision-making. As the organization grew and its analytics capabilities expanded, the data environment began to grow rapidly, which naturally increased its complexity, maintenance challenges, and processing costs.
Project objective
The main goal was to establish a modern, modular data architecture in BigQuery that would fully leverage the platform’s potential and ensure its scalability. The system was designed to create a solid foundation for massively scaling analytics and advanced Artificial Intelligence (AI) applications, allowing the team to focus entirely on implementing innovations.
Scope of work
Key activities:
- Strategic audit and data mapping
We conducted a comprehensive inventory and strategic audit of the entire BigQuery environment, enabling us to accurately map data dependencies and identify critical assets. This assessment served as the foundation for designing an architecture focused on maximizing performance, scalability, and long term development potential. - Implementation of a modern multi layer data model in Dataform
We designed and implemented a modern, multi layer data model based on Google Cloud Dataform, transforming the existing architecture into a more efficient and consistent platform. The new architecture follows a fully standardized approach and consists of the following logical layers:
- Source - flexible ingestion of raw technical data
- Staging - automated data cleansing and standardization (Data Quality)
- Intermediate - advanced business transformations, ready for predictive modelling
- Marts - business ready, subject oriented reporting models
This layered architecture provides greater transparency, scalability, and flexibility while enabling future development without impacting the stability of the overall platform.
- Data processing cost optimization
Key processing pipelines were redesigned to leverage incremental processing rather than reprocessing entire data volumes. By fully utilizing the capabilities of the Data Lake and optimizing data ingestion processes, we significantly improved performance while reducing processing costs. - Data orchestration and automation
We implemented a stable and fully automated data refresh orchestration using Google Cloud Dataform. This approach ensures process integrity, reliable dependency management, and consistently up to date, trustworthy data for business critical analytics. - Knowledge transfer and team enablement
We prepared a comprehensive set of best practices together with detailed technical documentation, enabling the Vasco team to independently maintain and further develop the platform in a cost efficient and sustainable way.
Results
Key results:
- Reduced daily BigQuery costs from approximately USD 100 to just USD 12 (88% reduction)
- Established a centralized and well structured data platform designed for future scalability
- Delivered stable and predictable data processing workflows capable of handling large data volumes
- Achieved full transparency across both business and technical data logic
Business value:
- Enabled the Vasco team to focus on innovation, predictive analytics, and future AI and Machine Learning initiatives thanks to a transparent and high performance data architecture
- Significantly reduced operational costs while improving data quality and reliability, creating a trusted Single Source of Truth
- Built a flexible and scalable foundation for future analytics, process automation, and the continued digital growth of the organization
Client feedback
Alterdata conducted a detailed assessment of our BigQuery environment and designed an architecture that streamlined its complexity and improved key processes. The transition to a multi-tier model in Dataform and the optimization of data ingestion yielded tangible savings and significantly simplified the analytics team’s ongoing work.
Alterdata conducted a detailed assessment of our BigQuery environment and designed an architecture that streamlined its complexity and improved key processes. The transition to a multi-tier model in Dataform and the optimization of data ingestion yielded tangible savings and significantly simplified the analytics team’s ongoing work.
Summary
The project for Vasco Electronics is an example of how strategic modernization and optimization of the data architecture in Google BigQuery can transform potential into a future-proof, scalable foundation for innovation. Our efforts not only established a fully transparent environment and reduced costs by over 88% by optimizing the use of BigQuery resources, but above all, they equipped the client with a modern, efficient data platform ready to harness the potential of AI/ML and support unlimited business scaling.
If your organization is developing data analytics capabilities or preparing to implement AI solutions, let us know. We’ll help you build a modern and scalable data architecture that will lay a solid foundation for your business’s future growth.
