AWS Machine Learning Blog

FEBRUARY 24, 2023

The solution is then able to make predictions on the rest of the training data, and route lower-confidence results for human review. In this post, we describe our design and implementation of the solution, best practices, and the key components of the system architecture.

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Smart Data Collective

JUNE 10, 2022

In this role, you would perform batch processing or real-time processing on data that has been collected and stored. As a data engineer, you could also build and maintain data pipelines that create an interconnected data ecosystem that makes information available to data scientists. Applications Architect.

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AWS Machine Learning Blog

NOVEMBER 12, 2024

The first step in developing and deploying generative AI use cases is having a well-defined data strategy. Agmatix’s technology architecture is built on AWS. Their data pipeline (as shown in the following architecture diagram) consists of ingestion, storage, ETL (extract, transform, and load), and a data governance layer.

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phData

SEPTEMBER 18, 2024

As data and AI continue to dominate today’s marketplace, the ability to securely and accurately process and centralize that data is crucial to an organization’s long-term success. Fivetran’s Hybrid Architecture allows an organization to maintain ownership and control of its data through the entire data pipeline.

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phData

FEBRUARY 5, 2024

Migrating Your Pipelines and Code It’s more than likely that your business has years of code being used in its data pipelines. Manually converting this code to work in Snowflake can be very challenging with differences in data processing paradigms, query languages, and overall system architecture.

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The MLOps Blog

MARCH 12, 2024

Data and workflow orchestration: Ensuring efficient data pipeline management and scalable workflows for LLM performance. Caption : RAG system architecture. Prompt-response management: Refining LLM-backed applications through continuous prompt-response optimization and quality control.

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