Despite the explosion of 'talk to your data' agents, most fall short of production-grade accuracy — here's why the problem is architectural, not just about better LLMs.
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Learn from Kaycee Lai, CEO and Founder of Promethium, How an AI-Enhanced Data Fabric Speeds the Creation of Data Products at F500 companies.
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In our last blog in this series, we took a deeper dive into the components that make up a Data Fabric and Data Mesh. If you look closely,...
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Discover the key components of a Data Mesh, including data domains, products, product owners, self-serve data platform, data governance, fed
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When it comes to managing access to data on an organizational level, there are a number of models that are used the latest is data fabric.
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Of all recent developments in data management, the data fabric may be the most compelling for a number of reasons. For example, it promises
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A data fabric creates a virtual layer that joins all of an organization’s data with the process and platforms necessary for decisionmaking.
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The growth and increasing complexity of enterprise data architectures have created a need for the ability to query multiple dataset.
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Learn the differences, pros and cons of a data fabric and data virtualization. Which use cases make sense for each and how to apply them.
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The Data Mesh concept is hyped as a counterpoint to the traditional large, centralized data platforms of the past few decades.
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A federated query is joining data from two or more disparate data sources. Example, joining data from Salesforce with data from an Oracle.
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What makes Data Fabric data pipelines so special is that they don't rely on persisting data first.
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The Data Fabric concept pushes beyond traditional thinking and is a big idea for changing the way data is made accessible.
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