Snowflake is committed to helping our customers unlock the power of artificial intelligence (AI) to drive better decisions, improve productivity and reach more customers using all types of data. Large Language Models (LLMs) are a critical component of generative AI applications, and multimodal models are an exciting category that allows users to go beyond text and incorporate images and video into their prompts to get a better understanding of the context and meaning of the data.

In this blog series, I am exploring the “sliding doors”, or divergent paths, for creating value with data across different use cases, practices, and strategies. In this post, I want to discuss how to generate value with Data Products. As I reviewed in my last blog, grabbing the door to the better path for managing your data isn’t just about solving your particular use case: it’s ultimately about delivering value for your business.

Executives across various industries are under pressure to reach insights and make decisions quickly. This is driving the importance of streaming data and analytics, which play a crucial role in making better-informed decisions that likely lead to faster, better outcomes.

Palo Alto Networks used BigQuery ML to automatically identify and label the owner, environment, and cost center for each of its cloud projects.

Data engineers and architects are being asked to do more with their enterprise data than ever before. Yet, the knowledge gap between what businesses want to do with data and how they can accomplish it is growing daily—especially considering today's AI hype cycle. With all that noise in the market, it's easy to see how organizations struggle to keep pace with innovation.

Welcome back to Yellowfin Japan’s ‘How to?’ blog series! In our previous blog, we went through how to create big number and vertical column charts in Yellowfin, and the many different charting options available in Yellowfin Canvas. Before we re-visit our regular series, we want to share a shorter dashboard walkthrough.

Enterprise Strategy Group compared BigQuery to alternative cloud-based enterprise data warehouse solutions.

With the GA of Apache Spark stored procedures in BigQuery, users can extend their queries with Spark-based data processing via BigQuery APIs.

The editorial team of Hitachi Vantara sat down for an interview with our Chief Product Officer, Octavian Tanase, to learn about his vision and strategy for AI in the enterprise.