BigQuery update on November 2, 2026 https://docs.cloud.google.com/bigquery/docs/release-notes#November_02_2026 #googlecloud You can now use BigQuery change history and continuous queries for Apache Iceberg managed tables in Lakehouse
November 2, 2026 at 8:20 PM
BigQuery update on November 2, 2026 https://docs.cloud.google.com/bigquery/docs/release-notes#November_02_2026 #googlecloud You can now use BigQuery change history and continuous queries for Apache Iceberg managed tables in Lakehouse
Google Cloud: BigQuery data agent observability GA: monitor performance, adoption, latency, and costs
November 3, 2026 at 12:30 AM
Google Cloud: BigQuery data agent observability GA: monitor performance, adoption, latency, and costs
Free. No sign-up. No Docker. No server to deploy.
Bufflehead is a desktop app for Mac, Windows and Linux that lets your AI tool run read-only SQL on Parquet, CSV, Postgres, MySQL and BigQuery.
Search Bufflehead to download it.
Bufflehead is a desktop app for Mac, Windows and Linux that lets your AI tool run read-only SQL on Parquet, CSV, Postgres, MySQL and BigQuery.
Search Bufflehead to download it.
November 2, 2026 at 4:00 PM
Free. No sign-up. No Docker. No server to deploy.
Bufflehead is a desktop app for Mac, Windows and Linux that lets your AI tool run read-only SQL on Parquet, CSV, Postgres, MySQL and BigQuery.
Search Bufflehead to download it.
Bufflehead is a desktop app for Mac, Windows and Linux that lets your AI tool run read-only SQL on Parquet, CSV, Postgres, MySQL and BigQuery.
Search Bufflehead to download it.
BigQuery now lets admins set daily token quotas for LLM-backed SQL by project and user.
The project defaults are 200B input and 20B output tokens. Exhaustion blocks new LLM calls, but embedding functions are excluded. Token caps aren't dollar budgets; model pricing and job…
Read more on Kimbodo:
The project defaults are 200B input and 20B output tokens. Exhaustion blocks new LLM calls, but embedding functions are excluded. Token caps aren't dollar budgets; model pricing and job…
Read more on Kimbodo:
How to Control BigQuery AI Costs Without Breaking Production Workflows
What Happened BigQuery has made daily token quotas generally available for its LLM-backed SQL functions, giving administrators a way to limit generation activity at both project and user levels. When…
kimbodo.com
October 31, 2026 at 6:00 PM
BigQuery now lets admins set daily token quotas for LLM-backed SQL by project and user.
The project defaults are 200B input and 20B output tokens. Exhaustion blocks new LLM calls, but embedding functions are excluded. Token caps aren't dollar budgets; model pricing and job…
Read more on Kimbodo:
The project defaults are 200B input and 20B output tokens. Exhaustion blocks new LLM calls, but embedding functions are excluded. Token caps aren't dollar budgets; model pricing and job…
Read more on Kimbodo:
More details here
#BigQuery
- CA docs.cloud.google.com/bigquery/doc...
- AI.COUNT_TOKENS docs.cloud.google.com/bigquery/doc...
#AlloyDB
docs.cloud.google.com/alloydb/docs...
#Bigtable
docs.cloud.google.com/bigtable/doc...
#GeminiEnterprise
docs.cloud.google.com/gemini/enter...
#BigQuery
- CA docs.cloud.google.com/bigquery/doc...
- AI.COUNT_TOKENS docs.cloud.google.com/bigquery/doc...
#AlloyDB
docs.cloud.google.com/alloydb/docs...
#Bigtable
docs.cloud.google.com/bigtable/doc...
#GeminiEnterprise
docs.cloud.google.com/gemini/enter...
October 30, 2026 at 9:22 AM
Google Cloud: BigQuery now queries Databricks-managed Apache Iceberg tables via Lakehouse
October 30, 2026 at 6:15 PM
Google Cloud: BigQuery now queries Databricks-managed Apache Iceberg tables via Lakehouse
Claude CodeのOpenTelemetryをBigQueryに流してAIコーディングのコストと失敗を可視化する | ウェブの便利屋 #zenn
https://zenn.dev/web_benriya/articles/claude-code-opentelemetry-bigquery-observability
https://zenn.dev/web_benriya/articles/claude-code-opentelemetry-bigquery-observability
Claude CodeのOpenTelemetryをBigQueryに流してAIコーディングのコストと失敗を可視化する
zenn.dev
October 31, 2026 at 1:54 PM
Claude CodeのOpenTelemetryをBigQueryに流してAIコーディングのコストと失敗を可視化する | ウェブの便利屋 #zenn
https://zenn.dev/web_benriya/articles/claude-code-opentelemetry-bigquery-observability
https://zenn.dev/web_benriya/articles/claude-code-opentelemetry-bigquery-observability
This article provides a comprehensive guide for migrating Google BigQuery workloads to an open lakehouse architecture on AWS using Apache Iceberg, covering target architecture, step-by-step migration process, and real-world customer success stories.
Migrate Google BigQuery to an open lakehouse on AWS with Apache Iceberg
This article provides a comprehensive guide for migrating Google BigQuery workloads to an open lakehouse architecture on AWS using Apache Iceberg, covering target architecture, step-by-step migration process, and real-world customer success stories.
aws-news.com
November 2, 2026 at 5:25 PM
This article provides a comprehensive guide for migrating Google BigQuery workloads to an open lakehouse architecture on AWS using Apache Iceberg, covering target architecture, step-by-step migration process, and real-world customer success stories.
📊 **BigQuery to Databricks: A Strategic Framework**
Migration as a strategic evolutionMany organizations support a range of data and analytics workloads on BigQuery today...
📰 Source: Databricks
🔗 Link: https://www.databricks.com/blog/bigquery-databricks-strategic-framework
#datascience
Migration as a strategic evolutionMany organizations support a range of data and analytics workloads on BigQuery today...
📰 Source: Databricks
🔗 Link: https://www.databricks.com/blog/bigquery-databricks-strategic-framework
#datascience
BigQuery to Databricks: A Strategic Framework
Discover best practices for migrating BigQuery data, scripts, and stacks to Databricks. Learn to optimize ROI and governance during your architectural evolution.
www.databricks.com
October 29, 2026 at 3:24 PM
📊 **BigQuery to Databricks: A Strategic Framework**
Migration as a strategic evolutionMany organizations support a range of data and analytics workloads on BigQuery today...
📰 Source: Databricks
🔗 Link: https://www.databricks.com/blog/bigquery-databricks-strategic-framework
#datascience
Migration as a strategic evolutionMany organizations support a range of data and analytics workloads on BigQuery today...
📰 Source: Databricks
🔗 Link: https://www.databricks.com/blog/bigquery-databricks-strategic-framework
#datascience
📰 New article by Saman Irfan, Ryan Jadidi, Siddhu Kolappan
Migrate Google BigQuery to an open lakehouse on AWS with Apache Iceberg
#AWS #BigData
Migrate Google BigQuery to an open lakehouse on AWS with Apache Iceberg
#AWS #BigData
Migrate Google BigQuery to an open lakehouse on AWS with Apache Iceberg
Learn how to migrate Google BigQuery workloads to an open lakehouse on AWS built on Apache Iceberg and Amazon S3. This post explains why an open lakehouse future-proofs your data, presents the target architecture on AWS, and walks through a step-by-step migration: assess, design, convert, migrate, cut over, and optimize.
aws.amazon.com
November 2, 2026 at 5:26 PM
BigQuery update on October 30, 2026 https://docs.cloud.google.com/bigquery/docs/release-notes#October_30_2026 #googlecloud You can now retrieve query results directly in the Apache Arrow format for faster retrieval speed and improved serialization efficiency
October 30, 2026 at 8:20 PM
BigQuery update on October 30, 2026 https://docs.cloud.google.com/bigquery/docs/release-notes#October_30_2026 #googlecloud You can now retrieve query results directly in the Apache Arrow format for faster retrieval speed and improved serialization efficiency
📢 New #updates · 2 Nov #16.4
· lightdash 3.128.0 — BigQuery workload identity federation support added
· GO Feature Flag cmd/wasm/v0.3.0 — Relay proxy upgraded to echo v5
· lightdash 3.128.0 — BigQuery workload identity federation support added
· GO Feature Flag cmd/wasm/v0.3.0 — Relay proxy upgraded to echo v5
November 2, 2026 at 10:40 PM
📢 New #updates · 2 Nov #16.4
· lightdash 3.128.0 — BigQuery workload identity federation support added
· GO Feature Flag cmd/wasm/v0.3.0 — Relay proxy upgraded to echo v5
· lightdash 3.128.0 — BigQuery workload identity federation support added
· GO Feature Flag cmd/wasm/v0.3.0 — Relay proxy upgraded to echo v5
The source, dated, on The Deploy Log:
https://deployedbyai.com/log/f45dc8844958/bigquery-databricks-iceberg-query/?k=br
https://deployedbyai.com/log/f45dc8844958/bigquery-databricks-iceberg-query/?k=br
October 30, 2026 at 6:15 PM
The source, dated, on The Deploy Log:
https://deployedbyai.com/log/f45dc8844958/bigquery-databricks-iceberg-query/?k=br
https://deployedbyai.com/log/f45dc8844958/bigquery-databricks-iceberg-query/?k=br
You can now monitor the performance, adoption, latency, and costs of your data agents and their conversations by using Google Cloud Observability in BigQuery. This feature is generally available (GA).
November 2, 2026 at 8:20 PM
You can now monitor the performance, adoption, latency, and costs of your data agents and their conversations by using Google Cloud Observability in BigQuery. This feature is generally available (GA).
October 27, 2026 at 3:59 PM
The source, dated, on The Deploy Log:
https://deployedbyai.com/log/8e3f765c0be8/bigquery-data-agent-observability/?k=br
Follow for one line every time AI actually ships, as it ships, 24/7.
https://deployedbyai.com/log/8e3f765c0be8/bigquery-data-agent-observability/?k=br
Follow for one line every time AI actually ships, as it ships, 24/7.
November 3, 2026 at 12:30 AM
The source, dated, on The Deploy Log:
https://deployedbyai.com/log/8e3f765c0be8/bigquery-data-agent-observability/?k=br
Follow for one line every time AI actually ships, as it ships, 24/7.
https://deployedbyai.com/log/8e3f765c0be8/bigquery-data-agent-observability/?k=br
Follow for one line every time AI actually ships, as it ships, 24/7.
Priya Verma explains that BigQuery stores your Search Console data beyond the 16-month limit and, when combined with GA4, connects search demand to on-site behaviour and conversions for a complete picture.
maj.to/471Kdcu
maj.to/471Kdcu
November 2, 2026 at 1:00 PM
Priya Verma explains that BigQuery stores your Search Console data beyond the 16-month limit and, when combined with GA4, connects search demand to on-site behaviour and conversions for a complete picture.
maj.to/471Kdcu
maj.to/471Kdcu
Priya Verma explains that SEO insights go far deeper than a spreadsheet of keywords and that BigQuery helps unlock the full story, and with AI helping interpret the data, upskilling here is well worth the investment.
maj.to/471Kdcu
maj.to/471Kdcu
November 2, 2026 at 3:00 PM
Priya Verma explains that SEO insights go far deeper than a spreadsheet of keywords and that BigQuery helps unlock the full story, and with AI helping interpret the data, upskilling here is well worth the investment.
maj.to/471Kdcu
maj.to/471Kdcu
BigQuery measures is now GA, unifying BI metrics and knowledge graphs for AI accuracy #googlecloud https://cloud.google.com/blog/products/data-analytics/bigquery-measures-ga-unifying-bi-metrics-and-knowledge-graphs/
BigQuery measures GA: Unifying BI metrics and knowledge graphs | Google Cloud Blog
BigQuery measures is now generally available, unifying BI metrics and knowledge graphs in one model so AI agents and dashboards share trusted data.
cloud.google.com
October 28, 2026 at 4:30 PM
BigQuery measures is now GA, unifying BI metrics and knowledge graphs for AI accuracy #googlecloud https://cloud.google.com/blog/products/data-analytics/bigquery-measures-ga-unifying-bi-metrics-and-knowledge-graphs/
Google Cloud BigQuery AI Integration: Architectural Advantage or Operational Bloat? + Video
Introduction: The push to integrate Artificial Intelligence natively into cloud enterprise warehouses like Google Cloud BigQuery promises unprecedented analytics capabilities alongside continuous automated…
Introduction: The push to integrate Artificial Intelligence natively into cloud enterprise warehouses like Google Cloud BigQuery promises unprecedented analytics capabilities alongside continuous automated…
Google Cloud BigQuery AI Integration: Architectural Advantage or Operational Bloat? + Video
Introduction: The push to integrate Artificial Intelligence natively into cloud enterprise warehouses like Google Cloud BigQuery promises unprecedented analytics capabilities alongside continuous automated model generation. However, embedding large language models (LLMs) and predictive analytics directly into core data pipelines creates severe architectural friction between immediate processing power and ballooning operational expenses. Organizations must balance the strategic benefits of autonomous data processing against the risks of unmanaged compute bloat, spiraling query costs, and shadow AI workflows.
undercodetesting.com
October 30, 2026 at 1:42 AM
Google Cloud BigQuery AI Integration: Architectural Advantage or Operational Bloat? + Video
Introduction: The push to integrate Artificial Intelligence natively into cloud enterprise warehouses like Google Cloud BigQuery promises unprecedented analytics capabilities alongside continuous automated…
Introduction: The push to integrate Artificial Intelligence natively into cloud enterprise warehouses like Google Cloud BigQuery promises unprecedented analytics capabilities alongside continuous automated…
Join Krishnan Saidapet & Madhavan Sridharan at #IBMTechXchange to see watsonx.data sync to BigQuery via Dataflow, cutting warehouse costs up to 50%. 🚀 Register → https://reg.tools.ibm.com/flow/ibm/techxchange26/attendeesessioncatalog/page/sessioncatalog_attendee/session/1781131060716001qhiV
[IBM TechXchange] Real-Time NoSQL to Cloud Analytics: Scaling watsonx.data and BigQuery with Google Cloud Dataflow
google.smh.re
October 29, 2026 at 7:43 PM
Join Krishnan Saidapet & Madhavan Sridharan at #IBMTechXchange to see watsonx.data sync to BigQuery via Dataflow, cutting warehouse costs up to 50%. 🚀 Register → https://reg.tools.ibm.com/flow/ibm/techxchange26/attendeesessioncatalog/page/sessioncatalog_attendee/session/1781131060716001qhiV
on October 28, 2026. Action required: To retain BigQuery access to Google SecOps data, configure export to a customer-managed BigQuery project (BYOBQ) or contact your account team to upgrade to Enterprise+.
October 28, 2026 at 4:40 PM
on October 28, 2026. Action required: To retain BigQuery access to Google SecOps data, configure export to a customer-managed BigQuery project (BYOBQ) or contact your account team to upgrade to Enterprise+.
Supported targets were Snowflake, Databricks, BigQuery, Fabric and MotherDuck.
I kind of feel validated once again for my decision to not rely on any vendor for business logic inside a transformation pipeline and just use plain SQL instead 🤷
I kind of feel validated once again for my decision to not rely on any vendor for business logic inside a transformation pipeline and just use plain SQL instead 🤷
November 2, 2026 at 6:47 AM
Supported targets were Snowflake, Databricks, BigQuery, Fabric and MotherDuck.
I kind of feel validated once again for my decision to not rely on any vendor for business logic inside a transformation pipeline and just use plain SQL instead 🤷
I kind of feel validated once again for my decision to not rely on any vendor for business logic inside a transformation pipeline and just use plain SQL instead 🤷