Mitigating Data Transfer Bottlenecks on Google Cloud: Best Practices for Cloud-to-Cloud and Cloud-to-On-Premises Connections
Abstract
Efficient data transfers between cloud platforms and on-premises systems are critical for optimizing real-time analytics, particularly when leveraging tools like BigQuery. Common challenges such as network latency, scalability, and managing large datasets can hinder performance. By implementing best practices like optimizing BigQuery configurations, automating ETL pipelines with tools such as Google Dataflow, and utilizing real-time data streaming, organizations can improve transfer efficiency and reduce latency. These strategies ensure seamless data ingestion, enabling faster and more accurate data processing, better scalability, and enhanced decision-making in cloud environments.
How to Cite This Article
Tulasiram Yadavalli (2020). Mitigating Data Transfer Bottlenecks on Google Cloud: Best Practices for Cloud-to-Cloud and Cloud-to-On-Premises Connections . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 1(2), 47-54. DOI: https://doi.org/10.54660/IJMOR.2020.1.2.47-54