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The Race For Data Quality in a Medallion Architecture

DataKitchen

This architecture is valuable for organizations dealing with large volumes of diverse data sources, where maintaining accuracy and accessibility at every stage is a priority. Bronze layers can also be the raw database tables. The Silver layer aims to create a structured, validated data source that multiple organizations can access.

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The Future of Business Intelligence is Open Source

Maxime Beauchemin

For those reasons, it is not surprising that it has taken over most of the modern data stack: infrastructure, databases, orchestration, data processing, AI/ML and beyond. That’s without mentioning the fact that for a cloud-native company, Tableau’s Windows-centric approach at the time didn’t work well for the team.

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Every Company is Becoming a Software Company

Confluent

Of course, this is not to imply that companies will become only software (there are still plenty of people in even the most software-centric companies), just that the full scope of the business is captured in an integrated software defined process. Here, the bank loan business division has essentially become software.

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CircleCI’s unnoticed holiday security breach

The Pragmatic Engineer

But today has been anything but a soft landing for customers of CircleCI, who got the email you always dread from a vendor, suggesting CircleCI was compromised and customers' secrets could have been accessed by an attacker during the past two weeks. These may be stored in project environment variables or in contexts.

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Serverless Data Pipelines On DataCoral

Data Engineering Podcast

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode.

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10 Lessons from 10 Years of Innovation and Engineering at Picnic

Picnic Engineering

A decade ago, Picnic set out to reinvent grocery shopping with a tech-first, customer-centric approach. For instance, we built self-service tools for all our engineers that allow them to handle tasks like environment setup, database management, or feature deployment effectively.

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Building a maintainable and modular LLM application stack with Hamilton

Towards Data Science

The example we’ll walk you through will mirror a typical LLM application workflow you’d run to populate a vector database with some text knowledge. This data will move through different services (LLM, vector database, document store, etc.) Store embeddings in a vector database, either LanceDB , Pinecone , or Weaviate.