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Which IDEs do software engineers love, and why?

The Pragmatic Engineer

It’s been nearly 6 months since our research into which AI tools software engineers use, in the mini-series, AI tooling for software engineers: reality check. Data from early adopters tends to indicate where innovation is within tooling. ‘The engineering team as a whole is upwards of 50 people.

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Top 11 GenAI Powered Data Engineering Tools to Follow in 2025

Analytics Vidhya

What will data engineering look like in 2025? How will generative AI shape the tools and processes Data Engineers rely on today? As the field evolves, Data Engineers are stepping into a future where innovation and efficiency take center stage.

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Data Engineering Roadmap, Learning Path,& Career Track 2025

ProjectPro

Data Engineering is gradually becoming a popular career option for young enthusiasts. That's why we've created a comprehensive data engineering roadmap for 2023 to guide you through the essential skills and tools needed to become a successful data engineer. Let's dive into ProjectPro's Data Engineer Roadmap!

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Top 10 Data Engineering & AI Trends for 2025

Monte Carlo

Here’s where leading futurist and investor Tomasz Tunguz thinks data and AI stands at the end of 2024—plus a few predictions of my own. 2025 data engineering trends incoming. Small data is the future of AI (Tomasz) 7. The lines are blurring for analysts and data engineers (Barr) 8. Table of Contents 1.

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The Ultimate Guide to Apache Airflow DAGS

With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer. This eBook provides a comprehensive overview of DAG writing features with plenty of example code.

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They Handle 500B Events Daily. Here’s Their Data Engineering Architecture.

Monte Carlo

A data engineering architecture is the structural framework that determines how data flows through an organization – from collection and storage to processing and analysis. It’s the big blueprint we data engineers follow in order to transform raw data into valuable insights.

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The Roots of Today's Modern Backend Engineering Practices

The Pragmatic Engineer

👋 Hi, this is Gergely with a bonus, free issue of the Pragmatic Engineer Newsletter. In every issue, I cover topics related to Big Tech and startups through the lens of engineering managers and senior engineers.   To succeed as a software engineer, you needed to be a jack-of-all-trades.

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A Guide to Debugging Apache Airflow® DAGs

In Airflow, DAGs (your data pipelines) support nearly every use case. As these workflows grow in complexity and scale, efficiently identifying and resolving issues becomes a critical skill for every data engineer. This is a comprehensive guide with best practices and examples to debugging Airflow DAGs.

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Apache Airflow® 101 Essential Tips for Beginners

Due to its widespread adoption, Airflow knowledge is paramount to success in the field of data engineering.

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Generative AI Deep Dive: Advancing from Proof of Concept to Production

Speaker: Maher Hanafi, VP of Engineering at Betterworks & Tony Karrer, CTO at Aggregage

💡 This new webinar featuring Maher Hanafi, VP of Engineering at Betterworks, will explore a practical framework to transform Generative AI prototypes into impactful products! There's no question that it is challenging to figure out where to focus and how to advance when it’s a new field that is evolving everyday.

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Improving the Accuracy of Generative AI Systems: A Structured Approach

Speaker: Anindo Banerjea, CTO at Civio & Tony Karrer, CTO at Aggregage

This can be especially difficult when working with a large data corpus, and as the complexity of the task increases. Using this case study, he'll also take us through his systematic approach of iterative cycles of human feedback, engineering, and measuring performance.

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)

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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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Agent Tooling: Connecting AI to Your Tools, Systems & Data

Speaker: Alex Salazar, CEO & Co-Founder @ Arcade | Nate Barbettini, Founding Engineer @ Arcade | Tony Karrer, Founder & CTO @ Aggregage

There’s a lot of noise surrounding the ability of AI agents to connect to your tools, systems and data. As an engineering leader, it can be challenging to make sense of this evolving landscape, but agent tooling provides such high value that it’s critical we figure out how to move forward.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.