We talk with Ben Tengelsen, Director of Data Products at Aampe, about why data sharing is core to Aampe's platform, how the team thought about build versus buy, and where analytics is headed next.

Dashboards that build themselves.

Context drift is poisoning your agentic analytics experience. Today, we fix it.

Practical use cases that are turning AI experiments into ROI generating investments this year.

Egress fees limit where you can sell, how fast you can grow, and how much margin you keep. Starting today, Bobsled radically reduces that tax—forever.

In this article, we’ll unpack what these models are, both in traditional and modern contexts, and why they are a critical concept for product managers at data companies to understand.

Semantic Model Sharing in Snowflake enables data product teams to distribute not just raw data, but also the business context that makes that data meaningful. When customers access data products through Snowflake Marketplace, they receive both the underlying datasets and semantic models that map business terminology to database schemas.

Filter rows, select columns, and build complex joins using a no-code editor or an AI-assisted SQL interface.