Media & Marketing

Author

Carlos Barge

BigQuery is a powerful tool for business intelligence and it offers analytics capabilities to organizations of all sizes. The platform’s flexible pricing structure, which is based on computing resources used and guarantees 100% utilization of available allocated resources, means that businesses can deploy the analytics and queries they need without having to rent out more server space or scale without a real need. Moreover, its real-time ingest and fast querying capacity make it ideal for a variety of use cases.

The platform has been utilized in real-time fraud detection, by leveraging its data gathering and organizational capacities. Some organizations use BigQuery to manage schema migrations and use batch ingest tools to update real-time data tables every few minutes.

Thanks to the platform’s expanded data capabilities—big query is built to manage petabyte-scale analytics—it also means that it can collect more data from disparate sources and organize it faster.

Additionally, combining BigQuery’s machine learning capabilities with existing datasets and structures can improve storage design, make for easier querying and data scanning, and even reduce costs by eliminating superfluous structures and optimizing storage based on individual organization’s usage patterns.

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