Google BigQuery

Mountain View, CA, USA
2010
May 19, 2022   |  By Carlos Augusto
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.
May 12, 2022   |  By Sean Lopp
BigQuery's Remote Functions (in preview) make it possible to apply custom cloud functions to your warehouse without moving data or managing compute. This flexibility unlocks many use cases including data enrichment. In this post we demonstrate a pattern for combining BigQuery with the Google Maps API to add drive times to datasets containing origin and destination locations. This enrichment pattern is easily adapted for address geocoding or adding Google Map's place descriptions to locations.
May 11, 2022   |  By Christopher Crosbie
Today we are announcing the Preview of BigQuery Remote Functions. Remote Functions are user-defined functions (UDF) that let you extend BigQuery SQL with your own custom code, written and hosted in Cloud Functions, Google Cloud’s scalable pay-as-you-go functions as a service. A remote UDF accepts columns from BigQuery as input, performs actions on that input using a Cloud Function, and returns the result of those actions as a value in the query result.
May 6, 2022   |  By Deepak Dayama
Customers who work with data warehouses, running BI on large datasets used to have to pick low latency but trading off freshness of data. With BigQuery BI Engine, they can accelerate their dashboards and reports that connect to BigQuery without having to sacrifice freshness of the data. Using the latest insights helps them make better decisions for the business.
Apr 26, 2022   |  By Clay Barrineau
In the exponentially growing data warehousing space, it is very important to capture, process and analyze the metadata and metrics of the jobs/queries for the purposes of auditing, tracking, performance tuning, capacity planning, etc. Historically, on-premise (on-prem) legacy data warehouse solutions have mature methods of collecting and reporting performance insights via query log reports, workload repositories etc. However all of this comes with an overhead of cost-storage & cpu.
Apr 14, 2022   |  By Joe Malone
IT leaders pick different clouds for many reasons, but the rest of the company shouldn’t be left to navigate the complexity of those decisions. For data analysts, that complexity is most immediately felt when navigating between data silos. Google Cloud has invested deeply in helping customers break down these barriers inherent in a disparate data stack. Back in October 2021, we launched BigQuery Omni to help data analysts access and query data across the barriers of multi cloud environments.
Apr 14, 2022   |  By Scott Ellis
Protecting sensitive data and preventing unintended data exposure is critical for businesses. However, many organizations lack the tools to stay on top of where sensitive data resides across their enterprise. It’s particularly concerning when sensitive data shows up in unexpected places – for example, in logs that services generate, when customers inadvertently send it in a customer support chat, or when managing unstructured analytical workloads.
Apr 8, 2022   |  By Jorge Vidaurre
At Mercado Libre, we are obsessed with unlocking the power and potential of data. One of our key cultural principles is to have a Beta Mindset. This means that we operate in a “state of beta”, constantly asking new questions of our data, experimenting with technologies and iterating our business operations in service of creating the best experiences for our customers.
Apr 8, 2022   |  By Polong Lin
Without a central place to manage models, those responsible for operationalizing ML models have no way of knowing the overall status of trained models and data. This lack of manageability can impact the review and release process of models into production, which often requires offline reviews with many stakeholders.
Apr 7, 2022   |  By Srinidhi Raghavan
Today, we are excited to announce the public preview of search indexes and related SQL SEARCH functions in BigQuery. This is a new capability in BigQuery that allows you to use standard BigQuery SQL to easily find unique data elements buried in unstructured text and semi-structured JSON, without having to know the table schemas in advance. By making row lookups in BigQuery efficient, you now have a powerful columnar store and text search in a single data platform.
May 5, 2022   |  By Google BigQuery
Cortex Data Foundation for SAP provides templates, solution content, deployment accelerators, and reference architecture to solve business problems. In this video, Lucia Subatin takes a deep dive into the technical details of Cortex Data Foundation for SAP by providing the recipe, ingredients, and some pro tips to deploy the data foundation solution content. Put on your chef’s hat and apron and get ready to start deploying!
Apr 21, 2022   |  By Google BigQuery
What is BigQuery and how can it help you gain new insights from your SAP data? In this video, Kevin Nelson, a Developer Advocate at Google Cloud, will demonstrate how to integrate your SAP data with BigQuery to help drive new insights across your organization and give more power to your data analytics users. Chapters: product: Cloud - General; fullname: Kevin Nelson;
Apr 7, 2022   |  By Google BigQuery
Are you interested in unlocking advanced analytics by replicating SAP data into BigQuery? In this video, Lucia Subatin, a Technical Lead in Solution Engineering, will demonstrate how to download and implement an ABAP enhancement built by Google Cloud to stream data directly into BigQuery. Watch, follow along, and ask questions in the comments below! Chapters: product: Cloud - General; fullname: Lucia Subatin;
Feb 22, 2022   |  By Google BigQuery
BigQuery can query terabytes of data, use familiar SQL, and only charge you for what you use! Take your data to the next level with the multifaceted bq command line tool. In this quickstart tutorial, Ryan Matsumoto demonstrates how to run queries and analyze data in BigQuery using the bq command line tool so that you can gain insights and make data-backed decisions to propel your organization.
Feb 11, 2022   |  By Google BigQuery
In this episode, Bruno revisits Geotab, a software-as-a-service-company that specializes in connective commercial vehicles and fleet management, to dig deeper into their data journey. Bob Bradley, Associate VP of Data and Solutions, shares the company's staggering growth (from 400,000 vehicles to well over 2 million in just 5 years) and how Google Cloud has helped them to keep up and stay ahead of the competition.
Jan 31, 2022   |  By Google BigQuery
Here to bring you the latest news in the Cloud is Debi Cabrera.
Nov 20, 2021   |  By Google BigQuery
Has your data team outgrown its on-premise traditional data warehouse? Are you looking for a system to store data that is secure, scalable, and cost effective? In this episode of Architecting with Google Cloud, Priyanka Vergadia speaks with Gary Morreale, the Director of Data Services from Independence Blue Cross about how his team migrated from Terradata to Bigquery on Google Cloud Platform. Listen as Gary Morreale discusses his team’s giant undertaking on migrating dataware to BigQuery.
Nov 18, 2021   |  By Google BigQuery
Have you ever been asked to prepare a slide deck containing many data points? Maybe you sifted through the data yourself along with copying and pasting the data over and over again—talk about a huge time commitment. In this video, Leigha Jarett discusses how you can use Google Apps Scripts to automate data-driven slide development and save yourself a lot of time.
Aug 26, 2021   |  By Google BigQuery
Want to ensure that your BigQuery environment stays cost effective and secure? In this episode of BigQuery Spotlight, we’ll examine how monitoring your data warehouse can optimize costs, help you pinpoint which queries need to be optimized, and audit both data-sharing and access. Watch to learn how BigQuery gives you the flexibility to export any of these data sources back into your data warehouse for custom reporting.
Aug 19, 2021   |  By Google BigQuery
Want to become more scalable with programmatic data workflows? In this episode of BigQuery Spotlight, we’ll examine BigQuery APIs so you can manage data warehousing resources, and take action on your data, programmatically and effectively.

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.