BigQuery Omni Cuts Multi-cloud Log Ingestion, Analysis Costs

BigQuery Omni is a multi-cloud data analytics solution that lets you use BigLake tables to perform BigQuery analytics on data kept in Azure Blob Storage or Amazon Simple Storage Service (Amazon S3)

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Gathering log data: gathers log data from the applications and/or infrastructure of the enterprise. A popular method for gathering this data is to save it in an object storage program like Google Cloud Storage in JSONL file format.

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Normalization of log data: Various infrastructures and applications produce distinct JSONL files. The fields in each file are specific to the program or infrastructure that produced it

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Indexing and storage: To lower storage and query expenses and improve query performance, normalized data should be stored effectively

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Querying and visualization: Enable enterprises to run analytics queries to find known threads, abnormalities, or anti-patterns in the log data through querying and visualization

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Data lifecycle: While storage expenses persist, the usefulness of log data declines with age. A data lifecycle procedure must be established in order to maximize costs

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Minimal egress costs: By storing the data locally, you can avoid transmitting large amounts of unprocessed information between cloud providers

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