Boost BigQuery with Python: Managed Python UDFs now generally available
Managed Python User-Defined Functions (UDFs) in BigQuery let you define and execute Python scalar functions directly within your BigQuery SQL queries.
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Databox Skills Marketplace - Free AI Analytics Skills for Claude
The Databox Skills Marketplace is a free library of AI analytics skills and workflows - download them, connect your Databox data, and get structured reports inside Claude in seconds. How it works: connect Databox MCP to Claude, run a skill with a single prompt, and Claude writes the analysis from your live data. No exports. No copy-paste. No manual setup. What's in the marketplace: All free. All built on Databox MCP.
Snowflake CoCo: Welcome to the Agentic Enterprise
When business questions move faster than answers, teams need more than dashboards. They need AI agents that can break silos, add context, and turn trusted enterprise data into action. Meet Snowflake CoCo — built to help data teams and business users move from reactive reporting to strategic action. In the Agentic Enterprise, everyone can become a strategic force, shaping what the business does next.
Agentic Data Engineering: Self-Healing Pipelines for Real-Time Insight
Brittle pipelines and SLA firefighting hold data teams back. Agentic data engineering introduces autonomous AI agents that detect failures, fix code, and re-run pipelines—with humans in the loop guide critical decisions. This video explains how Cloudera Data Engineering and Cloudera AI enable self-healing pipelines.
Fivetran named a Leader for the fifth consecutive year in Snowflake's 2026 Modern Marketing Data Stack report
This recognition reflects the critical role automated data movement continues to play in helping organizations unify data, improve decision-making, and prepare for the future of AI.
Fivetran vs. Airbyte: Features, pricing, services, and more
Compare Fivetran vs Airbyte pricing and key features. Learn how to choose the right data integration platform for you.
What is ETL? A simple guide to the ETL process and how it works
Understand what ETL is, how the ETL process works in three steps, and why data integration is essential for turning raw data into analytics-ready insights.
Pre-Packaged Inference, Production-Grade: AMD AIMs with ClearML
Running production LLM inference on a new accelerator family is a layered problem. The model matters. The runtime that exists for the GPU you have matters at least as much. So does the precision mode that works without losing accuracy, the inference engine that hits your throughput targets, and the secure endpoint the rest of your stack can actually call. The entire stack underneath the model is where most of the real engineering work lives and where the cost of getting it wrong shows up first.
Explainable AI in Customer-Facing Analytics: How Yellowfin Turns Predictions into Action
Predictions alone are no longer enough. A churn score is not useful if no one trusts it, and a risk score does not help if the next step is unclear. The same goes for a recommendation engine. People need to know why a model made a call, and what action comes next. That is the core shift in explainable AI for analytics. The work has moved from “what happened?” to “why did it happen, and what should I do now?” Customer-facing analytics depends on that shift.
10 Best Google Data Studio (formerly Looker Studio) Alternatives for Analytics in 2026
On April 11, 2026, Google renamed Looker Studio back to Data Studio to end years of confusion with the enterprise Looker product. The rename did not change the underlying architecture: Data Studio remains a visualization layer, not a data integration platform. That means the moment you need sources beyond Google Analytics, Google Ads, and BigQuery, you are handling extraction, transformation, schema changes, and cross-platform normalization on your own, or paying for connectors that do it for you.