Getting started with Google BigQuery
Let’s start first talking what is data warehouse: According to AWS: A data warehouse is a central repository of information that can be analyzed to make better informed decisions. So basically, it is

I build robust solutions from start to finish. With over 9 years of experience, I transform complex problems into scalable cloud architectures, efficient data pipelines, and high-performance user interfaces. I write code, design infrastructure, and deliver production-ready products.
Sharing my thoughts on architecture, backend and data.
Let’s start first talking what is data warehouse: According to AWS: A data warehouse is a central repository of information that can be analyzed to make better informed decisions. So basically, it is
Design and deployment of cloud-native data platforms and ETL/ELT pipelines.
Business logic development, LLM integration for data enrichment, and secure backend architectures.
Creation of modern, fast, and scalable web interfaces for product analytics and end-user interaction.
Deployment automation, containerization, and reliable infrastructure maintenance.
Hands-on Builder & Problem Solver
Architecture of dbt transformations for analytical datasets in BigQuery and Snowflake. OpenAI LLM integration to automate insights and CI/CD pipeline optimization.
Early development of ayenda.com using Next.js and GraphQL. Full management of backend infrastructure, VPN, and automated deployment pipelines.
Backend architecture and development for an online dance lesson platform. Deployment of containerized solutions using Docker Compose.