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2013

ETL

How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Flipboard

NOVEMBER 24, 2023

Let’s combine these suggestions to improve upon our original prompt: Human: Your job is to act as an expert on ETL pipelines. Specifically, your job is to create a JSON representation of an ETL pipeline which will solve the user request provided to you.

Database

Database AWS ETL SQL

Monitor embedding drift for LLMs deployed from Amazon SageMaker JumpStart

AWS Machine Learning Blog

FEBRUARY 2, 2024

The embeddings are captured in Amazon Simple Storage Service (Amazon S3) via Amazon Kinesis Data Firehose , and we run a combination of AWS Glue extract, transform, and load (ETL) jobs and Jupyter notebooks to perform the embedding analysis. Set the parameters for the ETL job as follows and run the job: Set --job_type to BASELINE.

AWS

AWS Clustering ETL Database

Data Lineage Through the Decades: Where It’s Going (And Where It’s Been)

Alation

FEBRUARY 7, 2023

It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a data warehouse project. Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company.

Data Warehouse

Data Warehouse ETL Business Intelligence Business Intelligence

Webinars

Automation, Evolved: Your New Playbook For Smarter Knowledge Work

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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

Monitor embedding drift for LLMs deployed from Amazon SageMaker JumpStart

Data Lineage Through the Decades: Where It’s Going (And Where It’s Been)

Webinars

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