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Google BigQuery

Announcing new BigQuery capabilities to help secure sensitive data

In order to better serve their customers and users, digital applications and platforms continue to store and use sensitive data such as Personally Identifiable Information (PII), genetic and biometric information, and credit card information. Many organizations that provide data for analytics use cases face evolving regulatory and privacy mandates, ongoing risks from data breaches and data leakage, and a growing need to control data access.

Introducing Firehose: An open source tool from Gojek for seamless data ingestion to BigQuery and Cloud Storage

Indonesia’s largest hyperlocal company, Gojek has evolved from a motorcycle ride-hailing service into an on-demand mobile platform, providing a range of services that include transportation, logistics, food delivery, and payments. A total of 2 million driver-partners collectively cover an average distance of 16.5 million kilometers each day, making Gojek Indonesia’s de-facto transportation partner.

Transform satellite imagery from Earth Engine into tabular data in BigQuery

Geospatial data has many uses outside of traditional mapping, such as site selection and land intelligence. Accordingly, many businesses are finding ways to incorporate geospatial data into their data warehouses and analytics. Google Earth Engine and BigQuery are both tools on Google Cloud Platform that allow you to interpret, analyze, and visualize geospatial data.

How to simplify AI models with Vertex AI and BigQuery ML

Did you know there is native integration between Vertex AI and BigQuery ML? With unified cloud data, your machine learning pipelines will have multiple options for training and storing/accessing data. Watch along and learn about the new native integrations between Vertex AI and BigQuery ML for Google Cloud.

Accelerating BigQuery migrations with automated SQL translation

Google’s data cloud enables customers to drive limitless innovation and unlock the value of their data via its robust offerings under a single, unified interface. By migrating their data ecosystems to Google Cloud, organizations are able to break down their data silos and harness the full potential of their data. However, historically, migrating data warehouses has not been an easy task.

Built with BigQuery: Gain instant access to comprehensive B2B data in BigQuery with ZoomInfo

Editor’s note: The post is part of a series highlighting our partners, and their solutions, that are Built with BigQuery. To fully leverage the data that’s critical for modern businesses, it must be accurate, complete, and up to date. Since 2007, ZoomInfo has provided B2B teams with the accurate firmographic, technographic, contact, and intent data they need to hit their marketing, sales, and revenue targets.

Built with BigQuery: Material Security's novel approach to protecting email

Since the very first email was sent more than 50 years ago, the now-ubiquitous communication tool has evolved into more than just an electronic method of communication. Businesses have come to rely on it as a storage system for financial reports, legal documents, and personnel records. From daily operations to client and employee communications to the lifeblood of sales and marketing, email is still the gold standard for digital communications.

Unlock real-time insights from your Oracle data in BigQuery

Relational databases are great at processing transactions, but they’re not designed to run analytics at scale. If you're a data engineer or a data analyst, you may want to continuously replicate your operational data into a data warehouse in real time, so you can make timely, data driven business decisions.