BigQuery – a powerful, cloud-based data warehouse solution from Google

BigQuery services from zweipunkt

Data integration & ETL processes

We help businesses connect and integrate a wide variety of data sources into BigQuery. We also develop and optimise ETL and ELT processes to ensure efficient and high-performance data processing.

Data Modelling & Architecture

We develop scalable and optimised data models that enable fast and cost-effective analysis. We also consult on the optimal data warehouse architecture based on BigQuery to ensure the best possible performance.

Cost and performance optimisation

We analyse and optimise queries in BigQuery to reduce latency and cut costs. Through the targeted use of partitioning and clustering, we improve the performance and efficiency of data queries.

Automation & Data Pipelines

We develop automated data pipelines that enable seamless and scalable data processing. By using Cloud Functions or Dataform, processes can be efficiently automated and operational overhead minimised.

Advanced Analytics & Machine Learning

We implement AI/ML models directly in BigQuery using BigQuery ML. We also develop predictive analytics and anomaly detection to optimise data-driven decision-making.

BigQuery: A data warehouse without the need for your own server infrastructure

BigQuery processes complex queries across vast amounts of data in seconds and offers maximum flexibility thanks to its serverless architecture. Businesses benefit from automatic scaling, built-in machine learning support, and native capabilities for streaming data and advanced SQL analytics. Thanks to deep integration with other Google Cloud services, data can be seamlessly linked, analysed and utilised efficiently.

Why choose zweipunkt as your Google BigQuery agency?

With zweipunkt as their BigQuery agency, businesses benefit from an experienced partner offering in-depth expertise in data warehousing, analytics and automation.

We not only provide support with technical implementation, but also ensure the optimal use and scaling of BigQuery – efficiently, cost-effectively and with a view to the future.