The Complete Guide to Events Tracking In Digital Analytics

Event tracking is critical to product analytics, providing deep insights into how users interact with your product. It involves monitoring and analyzing specific actions (events) users take within your application or website. These insights are pivotal for enhancing user experience, improving product features, and driving growth.

AI for Software Engineering Forecasting

New AI and Machine Learning (ML) solutions have become one of the most powerful tools in today’s technology stacks. These support the ability to process and analyze vast amounts of data to identify patterns and to make forecasting more reliable. AI has been driving innovation in healthcare, finance, and retail. Now, it's beginning to revolutionize the field of software engineering. This article shares some of our innovations in applying AI to software engineering processes.

AI-Powered Sales Assistant: The Future of Sales Productivity

Sales reps dedicate just two hours each day to active selling, according to HubSpot research. At Snowflake, our sales team found they were wasting 10 to 15 minutes searching for the right content every time they needed to answer a single question, like “Can you explain how Snowflake handles data integration from various sources?” Valuable content was scattered across different platforms, forcing employees to hop between various tools to assemble the right information.

Data Clean Rooms Explained: What You Need to Know About Privacy-First Collaboration

If you ask any advertiser about the most disruptive factor in recent years, they’ll probably hesitate between two contenders: privacy and AI. While AI is poised to have a transformative impact far beyond advertising in the future, one thing is certain: No organization today can address use cases involving consumer data without prioritizing privacy. Before we dive into the world of data clean rooms, let’s take a quick trip back in time to set the stage.

Navigating the Modern Data Landscape in 2025

In this webinar, industry expert will explore the latest trends in analytics, the growing impact of AI/ML, and the role of hybrid data infrastructures in modern data management. We’ll discuss the challenges of balancing legacy systems with modern cloud solutions and provide actionable insights to help organizations future-proof their data strategies. Whether you're looking to streamline data operations, enhance analytics capabilities, or align your data investments with business goals, this session will equip you with the knowledge to stay ahead in an ever-changing data ecosystem.

External IDE Connectivity: Access Spark from Your Favorite IDE with Cloudera Data Engineering

This demo showcases Cloudera Data Engineering's External IDE Connectivity, powered by the Spark Connect API. Data engineers can connect local IDEs like VS Code or Jupyter Lab to cloud clusters, run Spark workflows remotely, and sync code with GitHub. This feature enhances data engineering flexibility and productivity by streamlining CI/CD pipelines and enabling seamless synchronization between local and cloud environments, empowering downstream multi-functional analytics and AI.

Building AI Agents and Copilots with Confluent, Airy, and Apache Flink

From automating routine tasks to providing real-time insights to inform complex decisions, AI agents and copilots are poised to become an integral part of enterprise operations. At least that’s true for the organizations that can figure out how to supply large language models (LLMs) with real-time, contextualized, and trustworthy data in a secure and scalable way.