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Unlocking near real-time analytics with petabytes of transaction data using Amazon Aurora Zero-ETL integration with Amazon Redshift and dbt Cloud

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While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis.

ETL 138
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10 Best Data Engineering Books [Beginners to Advanced]

Pickl AI

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

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What is the Snowflake Data Cloud and How Much Does it Cost?

phData

This data mesh strategy combined with the end consumers of your data cloud enables your business to scale effectively, securely, and reliably without sacrificing speed-to-market. What is a Cloud Data Warehouse? For example, most data warehouse workloads peak during certain times, say during business hours.

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Architect a mature generative AI foundation on AWS

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For the preceding techniques, the foundation should provide scalable infrastructure for data storage and training, a mechanism to orchestrate tuning and training pipelines, a model registry to centrally register and govern the model, and infrastructure to host the model. She has presented her work at various learning conferences.

AWS 141
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How Reveal’s Logikcull used Amazon Comprehend to detect and redact PII from legal documents at scale

AWS Machine Learning Blog

Outside of work, he enjoys playing lawn tennis and reading books. Jeff Newburn is a Senior Software Engineering Manager leading the Data Engineering team at Logikcull – A Reveal Technology. He oversees the company’s data initiatives, including data warehouses, visualizations, analytics, and machine learning.

AWS 124
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Agentic AI and AI‑ready data: Transforming consumer‑facing applications

Dataconomy

From ordering groceries to booking travel, consumers will increasingly rely on AI agents to handle interactions that once required direct human effort. In other words, Snowplow s data pipeline can serve as the eyes and ears of your AI agents, feeding them the AI-ready behavioral data they need to make intelligent decisions.

AI 70
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What Are The Best Third-Party Data Ingestion Tools For Snowflake?

phData

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.