In 2024, organizations realized the revolutionizing business potential of gen AI. They accelerated their gen AI operationalization processes: explored new use cases to implement, researched LLMs and AI pipelines and contemplated underlying ethical issues. And with the seeds of the AI revolution now planted, the market is maturing accordingly.

Keboola, in cooperation with Capgemini and Snowflake, is releasing “AI Data Management For Dummies," a book written to be an easy introduction to the world of discriminative and generative AI.

Since 5G networks began rolling out commercially in 2019, telecom carriers have faced a wide range of new challenges: managing high-velocity workloads, reducing infrastructure costs, and adopting AI and automation. Because data management is a key variable for overcoming these challenges, carriers are turning to hybrid cloud solutions, which provide the flexibility and scalability needed to adapt to the evolving landscape 5G enables.

In the last year, we’ve seen the explosion of AI in the enterprise, leaving organizations to consider the infrastructure and processes for AI to successfully—and securely—deploy across an organization. As we head into 2025, it’s clear that next year will be just as exciting as past years. Here, Cloudera experts share their insights on what to expect in data and AI for the enterprise in 2025.

LLMs are the foundation of gen AI applications. To effectively operationalize and de-risk LLMs and ensure they bring business value, organizations need to consider not just the model itself, but the supporting infrastructure, including GPUs and operational frameworks. By optimizing them to your use case, you can ensure you are using an LLM that is the right fit to your needs.

From humble beginnings, Apache Kafka steadily rose to prominence and now sits as the backbone of data streaming for thousands of organizations worldwide. From its robust API, cloud-native implementations like Confluent Cloud, and synergy with other technologies like Apache Flink, Kafka has grown to cover many use cases across a broad range of industries.