Google BigQuery

Mountain View, CA, USA
2010
  |  By Vidya Shanmugam
We are excited that bidirectional data sharing between BigQuery and Salesforce Data Cloud is now generally available. This will make it easy for customers to enrich their data use cases by combining data across different platforms securely, without the additional cost of building or managing data infrastructure and complex ETL (Extract, Transform, Load) pipelines.
  |  By Luis Alonso
Introducing new BigQuery SQL features for performing two of the most common time-series operations: windowing and gap filling.
  |  By Gunjan Patel
Palo Alto Networks used BigQuery ML to automatically identify and label the owner, environment, and cost center for each of its cloud projects.
  |  By Lu He
With the GA of Apache Spark stored procedures in BigQuery, users can extend their queries with Spark-based data processing via BigQuery APIs.
  |  By Miguel de Luna
Enterprise Strategy Group compared BigQuery to alternative cloud-based enterprise data warehouse solutions.
  |  By Xi Cheng
You can now access Gemini 1.0 Pro from inside the BigQuery console, gaining scale and efficiency to ground LLMs with your business data.
  |  By Jobin George
Find out how Livesport reduced data engineering by 70% while increasing data activation with Dataddo and BigQuery.
  |  By Samarth Shah
BigQuery’s entity resolution framework lets customers integrate directly with the identity providers and match their records to an identity domain.
  |  By Gerrit Kazmaier
BigQuery now supports generative AI use cases using Gemini 1.0 Pro with Vertex AI, providing higher input/output scale and better result quality.
  |  By Omid Fatemieh
Vector search in BigQuery, or approximate nearest-neighbor search, enables AI use cases like semantic search, similarity detection, and RAG with LLMs.
  |  By Google BigQuery
Data and AI Cloud for Marketing: Your marketing, multiplied by Google Cloud Speakers: Jiby Varghese.
  |  By Google BigQuery
Duet AI can easily create SQL or Python code to do things like customer segmentation in BigQuery Studio.
  |  By Google BigQuery
If you’re working with large amounts of data, and looking for guidance on how to build a data warehouse in Google Cloud using BigQuery- this new Jump Start Solution is for you! In this video, we’ll walk you through the Jump Start Solution that combines BigQuery as your data warehouse and Looker Studio as a dashboard and visualization tool.
  |  By Google BigQuery
Welcome to Tutorial Time where we show you what you can learn from our interactive tutorials. In this tutorial you’ll learn how to export your Cloud Billing data to BigQuery for analysis.
  |  By Google BigQuery
In this episode of Radar Release, learn about the deeper interoperability between Google’s Earth Engine and BigQuery services. Learn about scaling large data while making it accessible to more users.
  |  By Google BigQuery
Highlights ways for developers and administrators to optimize their storage spend in BigQuery.
  |  By Google BigQuery
Highlights for developers and administrators how to optimize compute spend in BigQuery.
  |  By Google BigQuery
Highlights ways for developers and administrators to improve cost and performance of SELECT queries in BigQuery.
  |  By Google BigQuery
Analyzing your unstructured data, such as images and free-form text, has long required machine learning expertise to draw out insights. BigQuery and Vertex AI are changing that by bringing pre-trained machine learning capabilities to your unstructured data in BigQuery via the BigQueryML Inference Engine. In this video, we'll give you an overview of these capabilities and walk through a demo of how you can analyze and enhance your unstructured data, all with the familiarity of SQL and without ever leaving your data warehouse!
  |  By Google BigQuery
What’s new with Google Cloud? Welcome to our weekly series where we serve you the lowest latency news. This week, we’re talking about BigQuery Differential Privacy, the Data Cloud & AI Summit, and more!

BigQuery is Google's serverless, highly scalable, enterprise data warehouse designed to make all your data analysts productive at an unmatched price-performance. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL without the need for a database administrator.

Analyze all your data by creating a logical data warehouse over managed, columnar storage, as well as data from object storage and spreadsheets. Build and operationalize machine learning solutions with simple SQL. Easily and securely share insights within your organization and beyond as datasets, queries, spreadsheets, and reports. BigQuery allows organizations to capture and analyze data in real time using its powerful streaming ingestion capability so that your insights are always current, and it’s free for up to 1 TB of data analyzed each month and 10 GB of data stored.