Google BigQuery

Mountain View, CA, USA
2010
Oct 16, 2020   |  By Jenny Palomino
At Google Cloud, we’re invested in building data analytics products with a customer-first mindset. Our engineering team is thrilled to share recent feature enhancements and product updates that we’ve made to help you get even more value out of BigQuery, Google Cloud’s enterprise data warehouse.
Oct 14, 2020   |  By Amy Schembari
Understanding the data we collect is essential—it allows us to identify trends and uncover answers about our world. However, stories in our data frequently go untold. Large datasets are hard to share between research communities due to their size, security restraints, and complexity. Even if these datasets are accessible to users, the tools needed to query them often require deep technical knowledge.
Oct 14, 2020   |  By Jagan R. Athreya
October happens to be the month to celebrate World Smile Day when Harvey Ball, the inventor of the smiley face declared this day as such to give people a reason to smile. This month, BigQuery users have a lot of new reasons to smile about with the release of new user-friendly SQL capabilities now generally available.
Sep 2, 2020   |  By Shane Glass
Companies from every industry vertical, including finance, retail, logistics, and others, all share a common horizontal analytics challenge: How do they best understand the market for their products? Solving this problem requires companies to conduct a detailed marketing, sales, and finance analysis to understand their place within the larger market. These analyses are designed to unlock insights in a company's data that can help businesses run more efficiently.
Sep 2, 2020   |  By Rajesh Thallam
Google BigQuery was released to general availability in 2011 and has since been positioned as a unique analytics data warehousing service. Its serverless architecture allows it to operate at scale and speed to provide incredibly fast SQL analytics over large datasets. Since its inception, numerous features and improvements have been made to improve performance, security, reliability, and making it easier for users to discover insights.
Aug 13, 2020   |  By Brian Welcker
More than ever, businesses are making real-time, data-driven decisions based on information stored in their data warehouses. Today’s data warehouse requires continuous uptime as analytics demands grow and organizations require rapid access to mission-critical insights. Business disruptions from unplanned downtime can severely impact company sales, reputation, and customer relations.
Aug 13, 2020   |  By Jonathan Sheffi
Genomic data is some of the most complex and vital data that our customers and strategic partners like Mayo Clinic work with. Many of them want to work with genomic variant data, which is the set of differences between a given sample and a reference genome, in order to diagnose patients and discover new treatments. Each sample’s variants are usually stored as a Variant Call Format file, or VCF, but files aren’t a great way to do analytics and machine learning on these data.
Aug 11, 2020   |  By Tino Tereshko
BigQuery is used by organizations of all sizes, and to meet the diverse needs of our users, BigQuery offers highly flexible pricing options. For enterprise customers, BigQuery’s flat-rate billing model is predictable and gives businesses direct control over cost and performance. We’re now making the flat-rate billing model even more accessible by lowering the minimum size to 100 slots, so you can get started faster and quicker.
Jul 17, 2020   |  By Anna Epishova
When migrating a data warehouse to BigQuery, one of the most critical tasks is mapping existing user permissions to equivalent Google Cloud Identity and Access Management (Cloud IAM) permissions and roles. This is especially true for migrating from large enterprise data warehouses like Teradata to BigQuery. The existing Teradata databases commonly contain multiple user-defined roles that combine access permissions and capture common data access patterns.
Jul 14, 2020   |  By Debanjan Saha
Today, we are introducing BigQuery Omni, a flexible, multi-cloud analytics solution that lets you cost-effectively access and securely analyze data across Google Cloud, Amazon Web Services (AWS), and Azure (coming soon), without leaving the familiar BigQuery user interface (UI). Using standard SQL and the same BigQuery APIs our customers love, you will be able to break down data silos and gain critical business insights from a single pane of glass.
Aug 12, 2020   |  By Google BigQuery
In this video, you will learn how you can manage costs in BigQuery by setting a custom quota that specifies a limit on the amount of query data processed per day.
Jul 15, 2020   |  By Google BigQuery
In this video, you will learn how to write and run queries from BigQuery tables directly in the BigQuery web UI. Product: BigQuery; fullname: Alicia Williams;
Jun 15, 2020   |  By Google BigQuery
Here to bring you the latest news in the Cloud is Stephanie Wong Tune in every week for a new episode and let us know what you think of the latest announcements in the comments below! Product: BigQuery; fullname: Stephanie Wong;
May 27, 2020   |  By Google BigQuery
Want to know how to create and organize your data sets in BigQuery? In this video, we show how to utilize BigQuery, so you can visualize your data via charts. product: BigQuery; fullname: Roger Martinez;
May 20, 2020   |  By Google BigQuery
With BigQuery turning 10 this month, hear from some of the founding engineers about their experience working with product, and how the innovation has been helped transform internal and external stakeholders.
Feb 20, 2020   |  By Google BigQuery
In this video, we’ll introduce the BigQuery sandbox as a way to analyze data in BigQuery without providing a credit card, and show you how to set up your own sandbox.
Apr 26, 2019   |  By Google BigQuery
You don't have to be a data scientist or a developer to start using machine learning. Join Trevor and Stephanie as they show you how to easily get started with BigQuery Machine Learning, even without a Computer Science degree. Try it out for yourself!
Apr 19, 2019   |  By Google BigQuery
Improve your BigQuery SQL query times and reduce overall costs by partitioning and clustering your tables! Join Nick and Stephanie as they give a quick demo of how to set it up, use it to the fullest extent, and try it out for yourself!
Jan 17, 2019   |  By Google BigQuery
To get the best performance out of Cloud Bigtable, it is essential to think about how you compose your row key. In this episode of Cloud Performance Atlas, Colt McAnlis helps some fitness professionals with their Bigtable index performance. Will we have the performance to get an extra workout in? Stay tuned to find out!
Jan 3, 2019   |  By Google BigQuery
Bigtable is a scalable database service that in order to be as performant as possible, has to be local to a specific region. In this episode of Cloud Performance Atlas, Colt McAnlis helps some high fliers get their bigtable performance under control. Will their performance be cleared for landing? Stay tuned to find out!

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.