21datas supports data projects on Google Cloud, from data structure and analytics to artificial intelligence use cases.
- Define architecture and access
- Set up pipelines and analytical storage
- Connect BI and AI use cases
How can we build a Google Cloud platform that fits our use cases?Appointments
Design a platform around your use cases
BigQuery for analytics, Cloud Storage for files and Cloud Run for selected processing jobs can form the foundations of a data platform. Choices depend on sources, volumes, processing frequency and organizational requirements. Hosting region and access permissions are defined during scoping.
Connect architecture, BI and artificial intelligence
The platform should serve concrete needs such as reporting, analysis and data-connected assistants. Pipelines, analytical models and connectors are designed together. Cost and error monitoring, documentation and knowledge transfer are essential for operating the solution after delivery.
Frequently asked questions
Do we have to move our entire system to Google Cloud?
No. An architecture can retain existing applications and sources, transferring only the data needed for analytics. Options depend on available interfaces and security requirements.
How can we control costs?
Costs depend on storage, processing, queries and the services used. Scoping includes estimates, budgets and consumption monitoring. Provider fees remain separate from the 21datas service.