Systems | Development | Analytics | API | Testing

Interview Tips | How to Ace Your System Design Interview at Snowflake

Principal Software Engineer Polita Paulus is no stranger to Snowflake’s interview process. In this video, she offers a behind-the-scenes look at how to approach Snowflake's system design interviews with confidence and clarity. Drawing from her own experience, Polita shares practical strategies, insider tips, and a clear breakdown of what interviewers are really looking for. You’ll gain a better understanding of how to think through complex design challenges, communicate your ideas effectively, and showcase your technical strengths.

Interview Tips | How to Ace Your Coding Interview at Snowflake

Senior Software Engineer Khushboo Bhaitia takes you behind the scenes of Snowflake’s coding interviews, breaking down what to expect and how to succeed. In this video, Khushboo shares practical strategies, gives insider tips, and walks through a mock scenario to help you feel more confident and prepared. Get ready to COAST through the interview process, as Khushboo helps crack the code to success in Snowflake’s coding interviews.

Data and AI Predictions for 2025 with Joe Reis

Navigating the evolving landscape of data engineering in the age of AI? Join us as we delve into a crucial conversation with @JoeReisData renowned author of "Fundamentals of Data Engineering" and the highly anticipated "Mixed Model Arts." Joe shares his expert insights on why robust data modeling remains paramount, the urgent need for data teams to upskill in this new era, and the transformative potential of a universal semantic layer.

11 Best Free Retail Datasets for Machine Learning [UPDATED]

The retail industry has been shaped and fundamentally transformed by disruptive technologies in the past decade. From AI assisted customer service experiences to advanced robotics in operations, retailers are pursuing new technologies to address margin strains and rising customer expectations.

How to Manage Thousands of Real-Time Models in Production

Two years after Seagate first shared their AI and MLOps success story, the data storage leader is now revealing how far they've come since then. In this blog post, you’ll see how the team manages thousands of AI models in production with only a few team members. This is thanks to their AI factory, whichdoes the heavy lifting of automated processes like monitoring, testing, mocking and more.

Apache Iceberg: The Basics

Choosing the right storage format is crucial for optimizing performance, cost, and flexibility when working with cloud data. While file formats like Apache Parquet and Avro have been popular choices for storing data in data lakes, in recent years a new category called table formats has emerged to provide more management capabilities on top of these files. Among these, Apache Iceberg has been gaining significant adoption and momentum. So what exactly is Iceberg and why does it matter? Let’s dive in.

Why Google's Agent2Agent Protocol Needs Apache Kafka

Not long ago, I wrote about a growing problem in enterprise AI: agents that don’t talk to each other. You’ve got a customer relationship management (CRM) agent doing its thing, a data warehouse agent crunching numbers, a knowledge bot quietly surfacing documents—but none of them are sharing what they know. Instead of a smart, connected ecosystem, we’re stuck with isolated pockets of intelligence: an island of agents.