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.

After going legally blind at 21, Chad Foster’s life flipped on its head. He had to re-learn how to be an active participant in society, starting with finishing his university degree. His life-altering experience at 21 had changed the course of Chad’s life, teaching him to crave the uncomfortable experiences because that’s where growth lies.

What’s the Forecast? A look at data and AI in 2025 2025 is set to be a year of growth and change, particularly in the AI space. Over the last couple of years, AI has evolved from a niche technology to a driving force behind business strategies, innovation, and efficiency in almost every industry. Its impact is felt far and wide. It is not only shaping how we search for information, but how we digest and react to the world around us.

Businesses must be prepared to transform their data architecture to keep up with the pace of the industry as long-standing ideas about operational efficiency and the customer experience have changed too. That’s especially true in the travel industry, an industry that generates and consumes tremendous amounts of data: think booking your flight, finding the best price of your hotel stay, etc.

Data has so much promise, but organizations struggle to use it effectively, especially with the increasing complexity of managing large projects and the pressure of incorporating AI. On this episode of The AI Forecast, we’re joined by Simon Asplen-Taylor, the founder and CEO of DataTick and author of “Data and Analytics Strategy for Business”. Simon has spent years counseling organizations on getting their data right. In this episode, Simon shares the common missteps organizations experience with their data – with all roads leading back to data quality and a wild west of data collection across a business.

For the inaugural episode of Women Leaders in Technology on The AI Forecast, we’re joined by one of the top female leaders in the technology industry, Kari Briski - Vice President of AI Software Product Management at NVIDIA. Kari shares the stories and strategies that inform her leadership style–like GSD or “getting stuff done”–what it means to trust your instinct, and the advice she gives to young women embarking on a career in tech and to women further along who feel stuck where they are.

The AI explosion has led to non-stop hype cycles as the technology continues to develop. But AI is only as good as the data behind it. The threat of lousy data is bad AI. Andrew Brust, Founder and CEO of Blue Badge Insights, joins The AI Forecast to discuss the AI hype–and how to prevent what he calls an “artificial Charlatan” of bad AI. He emphasizes the dependent relationship between data and AI and the former’s role in the success of the latter. Specifically, he addresses the data governance conundrum, and why in order for data technology to be successful, it has to be fun.

More data exists than ever before – in fact, IDC predicts worldwide data will grow 61% by 2025. However, simply having data is not enough; business leaders must know how to effectively leverage it to make informed decisions. Conversely, data professionals also need strong business acumen to understand how their insights create value for the organization. Jordan Morrow, known as “The Godfather of Data Literacy,” joins The AI Forecast to share why data has become so complicated and what leaders and data professionals can do to untangle a messy data web for real value.

Data professionals are at the forefront of today’s digital economy, driving organizational transformation through AI. Yet, despite the vast opportunities AI presents, many data professionals encounter challenges that hinder their ability to lead effectively in this space.

An overview of how GenAI empowers Cloudera customers to drive impactful business outcomes, and how Cloudera AI makes it easier for organizations to deploy and scale AI successfully. We dive into powerful tools like Accelerators for Machine Learning Projects (AMPs), Cloudera AI Inference service, AI Assistants, and end-to-end GenAI platforms, all designed to accelerate your AI journey.