From the course: Introduction to Modern Data Engineering with Snowflake
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Delivery of data products - Snowflake Tutorial
From the course: Introduction to Modern Data Engineering with Snowflake
Delivery of data products
There's so much that is possible with clean, transformed data produced by a strong pipeline. Things like well-trained machine learning models, applications that present critical data to end users, datasets that enrich other use cases, and much more. In short, with ready-to-use transform data, we're at the stage of being able to deliver value and insights to consumers and other systems. And in this module, we'll dive into how to do this by exploring the third phase of our data engineering framework: delivery. What exactly do we mean by delivery? Before we get into the details, let's step back a little and contextualize everything that you've learned. You're learning to build data pipelines. If we oversimplify things for just a bit, we know that given an input, a data pipeline should produce an output. More tactically, the pipelines that you're building will take in raw data as an input, perform transformations against that data, and output or deliver something of value. For example…
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