Blog

Which architecture is right for your business? Using Zeotap as an example, we explain the difference between zero-copy access and a native Snowflake integration.

Composable customer data platforms (CDPs) have long been more than a marketing term, but not every composable CDP works the same way. Some access a company’s Snowflake data via zero-copy, while others run entirely natively within the company’s own account. Using Zeotap as an example, this article explores what distinguishes these approaches from both a technical and strategic perspective. By the end, you will understand which architecture is best suited to which use case—and what to consider during procurement.

SAP and Snowflake have been partners for some time. Now, SAP Business Data Cloud (BDC) and Snowflake are becoming even more tightly integrated. What many have long been waiting for is now possible: data sharing— including SAP semantics—as a foundation for analytics and AI. We explain the key fundamentals, show how hyperscalers fit into the picture, outline the available models, and walk through the technical implementation. Above all, we explore the opportunities this integration creates.

How do you develop a data strategy that moves beyond planning? This article uses the flywheel principle to show how concrete use cases, clear accountability, and visible business value can build lasting momentum.

AI use cases can be collected quickly, but prioritizing them is what determines their actual value. Learn how to cluster ideas effectively, build strategic capabilities, and establish a sound starting point with a Proof of Value.

A data roadmap does not have to be a rigid five-year plan. Learn how to structure your data journey across four sequential horizons, make value visible early, and keep business, people, and technology moving in sync.

How can small improvements in revenue, costs, and workflows have a disproportionately large impact on margins? Using a simple calculation, this article shows how data, AI, and automation can help you boost productivity in a targeted way.

What do Claude Monet and the quality of your company’s data have in common? This article explains why blurry, inconsistent data can distort decisions—and how to create a reliable foundation for management, analytics, and AI.

OData is the language your SAP system uses to talk to the world today. We'll show you step by step how to turn an idea into a production-ready, delta-capable OData service in S/4HANA or ECC.

Discover how Snowflake User-Defined Table Functions can bring data extraction into your dbt data pipelines. The article shows how to pull Salesforce data directly into Snowflake and materialize it in dbt models without a separate ingestion tool.

In the age of agentic AI, retrieval quality often determines how reliably a system performs. Using an AI staffing use case, we show how retrieval can be meaningfully improved with late interaction retrieval, cross-encoders, and LLM-based approaches.

Which Azure IoT solution fits which scenario? This article compares IoT Hub, IoT Edge, and Azure IoT Operations—and explains why OT-centric data flows are becoming increasingly important for physical AI and modern production environments.

We'll show you how to get to actionable insights and decisions faster with Snowflake Intelligence. And: How to realize use cases and increase the ROI of your data platform: with little effort and without technical know-how.