Function calling using LLMs
While LLMs excel at generating cogent text based on their training data, they may also need to interact with external systems. Function calling allows them to construct such calls. The LLM does not execute these calls directly, instead it creates a data structure that describes the call, passing that to a separate program for execution and further processing.
ReadDesigning Data Products
Working backwards from the end goal is a core principle of software development, and we've found it to be highly effective in modelling data products. In this article we'll explore a step-by-step, methodical approach to identifying data products that avoids overdesign while providing just enough clarity for teams to begin implementation.
ReadGoverning Data Products Using Fitness Functions
Decentralized data management requires automation to scale governance effectively. Fitness functions are a powerful automated governance technique we've applied to data products within the context of a Data Mesh. Since data products serve as the foundational building blocks of a data mesh, ensuring robust governance around them significantly increases the chances of a successful data mesh transformation.
ReadData Mesh in practice - Technology and the architecture (Part IV)
In the technology stream of our discovery process, data engineers engage with the domain that's being onboarded to understand their existing platform capabilities and the scope of any data products they already have in place. This helps identify the Data Mesh delta that will need to be bridged with new technology and architecture.
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