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.

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.

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.

What AI Approach is Right for You: LLM Apps, Agents, or Copilots?

The generative AI hype train doesn’t appear to be slowing down, with organizational adoption rising from 33% in 2023 to 78% by the end of 2024. In fact, bigger companies are leading the way in GenAI adoption, with the global AI market projected to grow annually by 36.6% between 2024 and 2030. However, GenAI growth isn’t following a linear path. Organizations are utilizing different AI approaches, depending on their specific use cases.

Prompt Engineering Best Practices You Should Know

Look around yourself. We are swarming in the world of data and AI. From students at school using ChatGPT to complete their assignments to professionals using AI for market research, content creation, or even debugging code, everyone is leveraging the power of large language models (LLMs). Mr. Smith isn’t Googling his tax questions anymore; he’s asking an AI assistant.

Cloudera and NVIDIA: Accelerating AI Innovation with Trusted Data at Scale

As organizations race to capitalize on AI, the foundation of success lies in trusted data and scalable infrastructure. In this video, we explore how Cloudera AI, powered by NVIDIA, delivers an end-to-end platform that enables organizations to build, test, and deploy high-performance AI solutions. From the Cloudera hybrid data lake to production-ready AI, discover how Cloudera is helping enterprises accelerate their data-driven future.

How to Build an AI Agent: A Step-By-Step Guide

A recent study by PwC suggests that AI could contribute up to $15.7 trillion to the global economy by 2030, with automation playing a key role in boosting efficiency and innovation. AI agents are central to this transformation, streamlining workflows, handling repetitive tasks, and enabling data-driven decision-making. From virtual assistants in customer service to intelligent fraud detection in finance, these agents are reshaping industries and driving business growth.

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.

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.