Google Bigquery is a fully-managed, serverless data warehouse designed for large-scale data analytics. It allows users to run fast SQL queries using the processing power of Google's infrastructure, enabling quick analysis of massive datasets without the need for managing physical hardware or database administration.
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About Google Bigquery
Google Bigquery was launched in 2011 as a part of Google Cloud Platform. It was developed to address the need for scalable, efficient data warehousing and analytics, leveraging Google's infrastructure to handle large datasets and complex queries quickly. The service aimed to simplify big data analysis by eliminating the need for managing physical hardware and database administration.
Strengths of Google Bigquery include its scalability, speed, and serverless architecture, which eliminate the need for infrastructure management. Weaknesses include potential high costs for large-scale queries and data storage. Competitors include Amazon Redshift, Microsoft Azure Synapse Analytics, and Snowflake.
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How to hire a Google Bigquery expert
A Google Bigquery expert must have strong SQL skills, experience with ETL (Extract, Transform, Load) processes, proficiency in data modeling and schema design, knowledge of BigQuery's specific functions and features, and familiarity with integrating BigQuery with other Google Cloud Platform services.
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$ 97K
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