GOOGLE BIGQUERY: YOUR BIG DATA BEST FRIEND

Google's robust, serverless data warehouse solution dazzles with its swift setup and seamless integration with other Google services.

 
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Why we choose Google BigQuery

 
High Interoperability
Seamless integration with other Google services like Looker.

 
Serverless Architecture
No need for infrastructure management, instantly ready for use.

 
Real-Time Analytics
Rapid SQL queries for immediate insights.

 
Scalability
Automatic scaling for any data volume, maintaining peak performance.
 

 
»BigQuery helps you load, process, and analyze data to inform critical business decisions - it's the backbone of many data-driven companies.«

 

Anja Schröder
Senior Consultant at Turbine Kreuzberg

BigQuery: Modern Data Warehouse Management

BigQuery is an analytics web service by Google, hosted on the Google Cloud Platform (GCP). It is a fully managed, serverless data warehouse perfect for querying, analyzing, and processing large datasets. Queries are executed using SQL, with native support for AI and machine learning.
Tailored for enterprises and business analytics in the big data and BI realm, BigQuery facilitates performant queries up to the petabyte scale. Storage and computational capacities are automatically scaled to meet demands. BigQuery supports real-time analytics, data encryption, and high availability.

How it works

  • Data Import: Import data from various sources such as CSV files, JSON files, Google Sheets, or directly through the BigQuery Data Transfer Service.
  • Storage: Data is stored in a columnar format, enhancing query efficiency and reducing storage requirements.
  • Querying: Use standard SQL to formulate complex queries, Googleexecuted on Google's distributed infrastructure.
  • Analysis: Seamlessly integrates with tools like Google Data Studio, Looker, and other BI tools for data visualization and analysis.
  • Security: Comprehensive security features, including data encryption at rest and in transit, and detailed IAM roles and permissions.

Features

  • Serverless architecture and scaling
  • Integrated SQL query language
  • Processing large datasets
  • Pay-as-you-go model
  • Fast data analysis

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