Modern Data 101

🎉 Introducing Modern Data 101 This is the beginning of the X page for Modern Data 101—your go to community for all things modern data. Our mission is simple: to empower data practitioners and leaders like you to extract unparalleled value from your data. Get more details 👇

🚀 Two Archetypes Of Data Engineers Kirill Bobrov explores the two main types of data engineers: the "businessy" & "techy" archetypes. Businessy focus on solving business problems, while Techy specialize in scalable infrastructure. Read more: tinyurl.com/yc48wxe6

🚀 Data Modelling Fundamentals: Normalisation, 3NF & Dimensional Modelling Pipelines to Insights Managed by Erfan Hesami & Hasan Geren explains key concepts in DB & data warehouse design. They contrasts normalisation with denormalisation. Read more: tinyurl.com/bdcnc34p

🚀Boost Your Big Data Workflow @anil_ozturkk explores leveraging Polars, a Rust-based DataFrame library, to optimize big data workflows. Polars offers multi-threaded processing, memory efficiency, & lazy evaluation. Read more: tinyurl.com/4zrduwj7

🚀C4 Modelling for Data Teams Andy Sawyer introduces the C4 model as a framework to simplify complex data architecture discussions. Originally developed for software systems, C4 model uses 4 layers-context, containers, components, & code. Read more: tinyurl.com/3f3drxjj

Discover a curated selection of top-notch data resources on the MD101 community website's resources page. Modern data resources: moderndata101.com/resources Check the for this week's top picks!

🚀 How to build scalable data lakes with Apache Iceberg @EcZachly explores the transformative potential of Apache Iceberg in building scalable data lakes. He highlights Iceberg's ability to support low-latency use cases. Read more: tinyurl.com/bp7cwtw3

🚀 Let's build a data platform like Spotify! Vu Trinh explores Spotify's approach to building a robust data platform to process over 1 trillion daily events. He highlights Spotify's transition from an on-premises infrastructure to Google Cloud Read more: tinyurl.com/yc65yxus

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The global market’s explosive growth reflects this reality: the future of AI innovation runs on Vector DBs. As we push the boundaries of AI, their importance will only grow. Are you ready for the vector revolution?

Why Should You Care About Vector Databases in the GenAI Era? Here’s a stat to chew on: the global Vector DB market is projected to hit $6.4B by 2030, growing at an incredible 22.3% CAGR —it's a sign of a seismic shift in how we handle data. But what's driving this growth? 🧵

Ready to level up your data game? Join the community & stay ahead of the curve: moderndata101.com/network

Thought Leadership - Beyond her advocacy, Adi shares her expertise through blogs, podcasts, and data conferences. With a strong presence on LinkedIn and X, she offers insights on best practices and emerging trends in data, AI, and tech.

🌟Data expert of the week: @AdiPolak🌟 Adi Polak, a catalyst for innovation in data streaming, AI, and developer advocacy. Adi has spent a better part of her career turning data into solutions.