Diving Deeper Into Data Engineering

Diving Deeper Into Data Engineering

?? We're kicking off 2025 with a newsletter focusing on one of the hottest topics: data. The following resources provide solutions for managing, storing, and optimizing all of your data.

Data Engineering: Enriching Data Pipelines, Expanding AI, and Expediting Analytics

Prepare for 2025 with these data engineering insights.

The 2024 Data Engineering Trend Report draws all former terminology, advancements, and discoveries into the larger picture, illustrating where we stand today along our unique, evolving data journeys. Within these pages, readers will find the keys to successfully build a foundation for fast and vast data intelligence across their organization. Our goal is for the contents of this report to help guide individual contributors and businesses alike as they strive for mastery of their data environments.

Real-Time Data Architecture Patterns

Discover the key data architecture patterns.

This Refcard focuses on architecture patterns for real-time data capabilities, beginning with an overview of data challenges, performance, and security and compliance. Readers will then dive into the key data architecture patterns — their components, advantages, and challenges — setting the stage for an example architecture, which demonstrates how to use open-source tools for a common real-time, high-volume data use case.

Open-Source Data Management Practices and Patterns

Learn how to build data architecture with open-source tools.

Open-source data architectures offer organizations and teams significant benefits, ranging from reduced vendor lock-in and improved cost effectiveness to greater scalability, availability, and flexibility. In this Refcard, you'll learn core practices for building an open-source data architecture stack, along with design patterns for infrastructure components, high availability, scalability, security, and more.

Data Architectures in the AI Era: Key Strategies and Insights

Check out this article to learn more about integrating data fabrics and meshes.

Data architecture is evolving rapidly due to the rise of GenAI, requiring companies to move away from data silos toward integrated data fabrics and data meshes. This transition can improve accuracy and largely benefit scalability and flexibility. However, there are also challenges to be aware of. Read the article here.

Fireside Chat: Unlocking Scalable Data Solutions With Open-Source Tools

Watch the Fireside Chat to learn more about your open-source options.

This session will provide practical insights into core open-source technologies like PostgreSQL, Apache Cassandra, and Apache Kafka, and guide participants through best practices for architecting scalable, high-performance systems. Key discussions will include infrastructure requirements, high availability strategies, performance optimization, and more, with real-world examples highlighting how these technologies can be leveraged to build resilient and cost-effective data solutions. Watch the Fireside Chat here.


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Lisa Sidlow

Connecting marketers with the developer, DevOps, SecOps, and AI audiences via integrated campaigns using content syndication, advertising, and content creation programs through DZone, a Technology Advice company.

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