As Large Language Models are revolutionizing natural language prompts, Large Vision Models (LVMs) represent another new, exciting frontier for AI. An estimated 90% of the world’s data is unstructured, much of it in the form of visual content such as images and videos. Insights from analyzing this visual data can open up powerful new use cases that significantly boost productivity and efficiency, but enterprises need sophisticated computer vision technologies to achieve this.

In an era where data is a critical business asset, securing it in B2B integration scenarios is more important than ever. This article explores the essential strategies and technologies for robust data security in B2B contexts. Data is a critical asset for businesses, which makes securing it during B2B integration more important than ever. This article will explore the best practices and tools that can aid in robust data security. Here are the 5 key takeaways from our B2B integration article.

Ensuring proper data governance and security relies on the capabilities offered by the software and platforms constituting your data infrastructure.

Because human-machine interaction using natural language is now possible with large language models (LLMs), more data teams and developers can bring AI to their daily workflows.

Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. While AI-powered, self-service BI platforms like ThoughtSpot can fully operationalize insights at scale by delivering visual data exploration and discovery, it still requires robust underlying data management. Now, that’s changing. Snowflake's new dynamic tables feature redefines how BI and analytics teams approach data transformation pipelines.

At 200 GB/hour, Fivetran HVR produced 27x lower latency and proved 63% less costly than Qlik Replicate.