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The Docker Compose of ETL: Meerschaum Compose

Towards Data Science

Docker was a game-changer, revolutionizing the way we design, build, and run our cloud applications. I use Compose daily at work and for my personal projects to build and manage my data pipelines, and today I’d like to show how you can build your ETL projects with Compose. mrsm compose run Registers the pipes and syncs them one-by-one.

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Measuring Technical Debt to Avoid the Boiling Frog Syndrome

Booking.com Engineering

Whether the changes are technical in nature, like an urgent security upgrade, or stem from a business need, such as building a new feature to make us more competitive in target markets — how fast we can change is critical. It’s only a question of how to identify, measure, and control it. How do we prevent this from happening?

Coding 98
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Implement Access Control in Node.js

nodeSWAT

Most web applications rely on some sort of access control to keep users from accessing information not meant for them. We have spent quite a few blog posts on various theories about security mechanisms for web applications ( Set Up a Secure Node.js Our aim, as usual, is to make the web a securer place for everyone.

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ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

AltexSoft

Whether your goal is data analytics or machine learning , success relies on what data pipelines you build and how you do it. In this article, we will explore the ELT process in detail, including how it works, its benefits, and common use cases. Order of process phases. Data engineering in 14 minutes. The ELT workflow.

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Best Data Observability Tools (with RFP Template and Analyst Reports)

Monte Carlo

This momentum shows no signs of stopping with data quality and reliability becoming a central topic in the data product and AI conversations taking place across organizations of all types and sizes. In other words, they help data teams be the first to know when data breaks and how to fix it. What are data observability tools?

BI 59
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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

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Dat: Distributed Versioned Data Sharing with Danielle Robinson and Joe Hand - Episode 16

Data Engineering Podcast

In order to provide a simpler way to distribute and version data sets among collaborators the Dat Project was created. In this episode Danielle Robinson and Joe Hand explain how the project got started, how it functions, and some of the many ways that it can be used.

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