New BigQuery editions: flexibility and predictability for your data cloud
When it comes to their data platforms, organizations want flexibility, predictable pricing, and the best price performance. Today at the Data Cloud & AI Summit, Google are announcing BigQuery editions with three pricing tiers — Standard, Enterprise and Enterprise Plus — for you to choose from,…
Secure and privacy-centric sharing with data clean rooms in BigQuery
Businesses across industries share data, combining first-party data with external sources to obtain new insights and collaborate with partners. In fact, 6000+ organizations share over 275 PBs of data across organizational boundaries every week using BigQuery. Last year, we launched in market Analytics Hub, built on…
How to do multivariate time series forecasting in BigQuery ML
Companies across industries rely heavily on time series forecasting to project product demand, forecast sales, project online subscription/cancellation, and for many other use cases. This makes time series forecasting one of the most popular models in BigQuery ML. What is multivariate time series forecasting? For…
Built with BigQuery: How Oden provides actionable recommendations with network resiliency to optimize manufacturing processes
Background The Oden Technologies solution is an analytics layer for manufacturers that combines and analyzes all process information from machines and production systems to give real-time visibility to the biggest causes of inefficiency and recommendations to address them. Oden empowers front-line plant teams to make effective decisions,…
How to use advance feature engineering to preprocess data in BigQuery ML
Preprocessing and transforming raw data into features is a critical but time consuming step in the ML process. This is especially true when a data scientist or data engineer has to move data across different platforms to do MLOps. In this blogpost, Google describe how we…
Demystifying BigQuery BI Engine
BigQuery BI Engine is a fast, in-memory analysis system for BigQuery currently processing over 2 billion queries per month and growing. BigQuery has its roots in Google’s Dremel system and is a data warehouse built with scalability as a goal. On the other hand BI…
Built with BigQuery: Lytics launches secure data sharing and enrichment solution on Google Cloud
Background and Context A Customer Data Platform (CDP) provides a monolithic view of the customer by collecting data from various sources to provide accessibility across different systems. CDPs are becoming increasingly vital as companies look to improve customer experience, engagement and personalization. Among the different…
How to deploy Tink for BigQuery encryption on-prem and in the cloud
Data security is a key focus for organizations moving their data warehouses from on-premises to cloud-first systems, such as BigQuery. In addition to storage-level encryption, whether using Google-managed or customer-managed keys, BigQuery also provides column-level encryption. Using BigQuery’s SQL AEAD functions, organizations can enforce a more granular level of…
Year in Review for BigQuery User Friendly SQL
In this year-end edition, Google are pleased to walk you through new SQL capabilities that Google launched in the categories of Enterprise Class, Data Quality and Schema Operations. Enterprise Class For our enterprise data analysts, we are pleased to share new capabilities in BigQuery SQL…
Break down data silos with the new cross-cloud transfer feature of BigQuery Omni
To help customers break down data silos, Google launched BigQuery Omni in 2021. Organizations globally are using BigQuery Omni to analyze data across cloud environments. Now, Google are excited to launch the next big evolution for multi cloud analytics: cross-cloud analytics. Cross-cloud analytics tools help analysts and…
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- Doubling calculation speed and other new innovations in Google Sheets
- Continued growth and success in the competitive logistics market
- How to get started with new Gemini model capabilities for Places API
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