The journey from a great idea for a Generative AI use case to deploying it in a production environment often resembles navigating a maze. Every turn presents new challenges—whether it’s technical hurdles, security concerns, or shifting priorities—that can stall progress or even force you to start over.

The new BigQuery jobs explorer lets you monitor, troubleshoot and optimize queries to make data-driven decisions to improve performance and costs.

Choosing the right business intelligence (BI) solution is pivotal for independent software vendors (ISVs) and enterprise organizations aiming for data-driven decision-making. But with so many preferences and use cases to account for, certain considerations can, initially, get overlooked. Centralized business intelligence (BI) is one such topic that requires careful preparation to achieve a nuanced understanding.

The new contribution analysis model in BigQuery lets you analyze metrics of interest from your dataset across defined test and control subsets.

According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making. More and more enterprises are leveraging pre-trained models for various applications, from natural language processing to computer vision. For that reason, Cloudera is evaluating a new line of business: Cloudera Integrated Data and AI Exchange (InDaiX).