Google's BigQuery is part of the Google Cloud Platform, a database-as-a-service (DBaaS) supporting the querying and rapid analysis of enterprise data.
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BigQuery is a fully managed, AI-ready data analytics platform that helps you maximize value from your data and is designed to be multi-engine, multi-format, and multi-cloud.
Store 10 GiB of data and run up to 1 TiB of queries for free per month.
BigQuery provides a single, unified workspace that includes a SQL, a notebook and a NL-based canvas interface for data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. Gemini in BigQuery provides AI-powered assistive and collaboration features including code assist, visual data preparation, and intelligent recommendations that help enhance productivity and optimize costs.
Serverless Apache Spark is available directly in BigQuery. BigQuery Studio lets users write and execute Spark without exporting data or managing infrastructure. BigQuery metastore provides shared runtime metadata for SQL and open source engines for a unified set of security and governance controls across all engines and storage types. By bringing multiple engines, including SQL, Spark and Python, to a single copy of data and metadata, the solution breaks down data silos.
BigQuery ML provides built-in capabilities to create and run ML models for BigQuery data. It offers a broad range of models for predictions, and access to the latest Gemini models to derive insights from all data types and unlock generative AI tasks such as text summarization, text generation, multimodal embeddings, and vector search. It increases the model development speed by directly applying ML to data and eliminating the need to move data from BigQuery.
Data governance is built into BigQuery, including full integration of Dataplex capabilities such as a unified metadata catalog, data quality, lineage, and profiling. Customers can use rich AI-driven metadata search and discovery capabilities for assets including dataset schemas, notebooks and reports, public and commercial dataset listings, and more. BigQuery users can also use governance rules to manage policies on BigQuery object tables.
| Deployment Types | Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Unspecified |
| Mobile Application | No |
Quick Data Analysis: Users appreciate the rapid query speed of Google BigQuery, enabling them to analyze massive datasets without long wait times. The fast query performance is a significant advantage highlighted by users for efficient data processing and analysis.
User-Friendly Interface: Many reviewers find Google BigQuery very user-friendly, allowing team members with varying levels of expertise to easily query data using simple language. The intuitive interface of Google BigQuery's editor and query builder is noted as helpful in quickly constructing new queries by users.
Seamless Integration: Users value the seamless integration of Google BigQuery with other tools like Google Cloud Storage and Data Studio, enhancing workflow efficiency and collaboration. This integration capability with various tools contributes to improved data management solutions according to users' feedback.
Challenge in Prompt Data Deletion: Users have encountered difficulties in promptly removing new data streams, which can lead to inefficiencies and waiting times during the deletion process. This issue may impact users' ability to manage their data effectively and maintain a streamlined workflow. Enhanced UI Visibility Needed: Several reviewers have suggested enhancing data visibility within a single page through UI improvements for better user experience. They seek clearer presentation of data on one screen without the need for excessive navigation, enabling quicker access to essential information. Simplified Security Integration Requested: Customers have called for easier management of security credentials and seamless Tableau integration without frequent re-authentication hassles. Simplifying security processes would enhance user convenience and potentially improve overall system usability.
