As organizations increasingly seek to enhance decision-making and drive operational efficiencies by making knowledge in documents accessible via conversational applications, a RAG-based application framework has quickly become the most efficient and scalable approach. As RAG-based application development continues to grow, the solutions to process and manage the documents that power these applications need to evolve with scalability and efficiency in mind. Until now, document preparation (e.g.

If innovation is the ultimate goal in business and technology today, then consider generative AI (gen AI) the vehicle taking us there — and a strong data strategy, the fuel. Despite all its promise of productivity gains and new discoveries, gen AI alone can't do it all. The technology needs a "very ready" data foundation to feed on, something the vast majority of businesses today (78%) do not possess, according to a new report by MIT Technology Review Insights, in partnership with Snowflake.

When scaling data science and ML workloads, organizations frequently encounter challenges in building large, robust production ML pipelines. Common issues include redundant efforts between development and production teams, as well as inconsistencies between the features used in training and those in the serving stack, which can lead to decreased performance. Many teams turn to feature stores to create a centralized repository that maintains a consistent and up-to-date set of ML features.

AI has profoundly impacted the life sciences industry for the past couple of decades. In the 2000s, researchers were able to use AI to analyze the human genome, identifying genetic markers and variations that could predict an individual’s susceptibility to certain diseases. This opened the door to personalized medicine and more effective therapies for genetic disorders.

Privacy is no longer a growing requirement for doing business — it's the new status quo. The stakes for not protecting it have only intensified. Consumers have been demanding greater control and privacy over their data for years, and now vast numbers are taking action to protect it, turning off tracking, using cookieless environments and relying on ad blockers at rapidly increasing rates.

There’s no question which technology everyone’s talking about in retail. Generative AI continues to promote incredible levels of interest with its promise of next-level productivity and new kinds of employee and customer experience. It’s all happening at light speed. When ChatGPT burst onto the scene, it gained hundreds of millions of users in a matter of months.

Data is increasingly becoming critical for the public sector — from guiding decisions in higher education to enhancing citizen services and streamlining government operations. Government agencies are overwhelmed with data, whether it be structured, like incident logs, or unstructured, like satellite images. Harnessing the vast amount of data can become a burden for any organization, yet the insights have the potential to significantly improve quality of life and strengthen national security.

As the frenzied hype around generative AI cools off and as we get into the year of ideation, earlier adopters of AI are starting to see the results of initial experimentation. And these conversations are increasingly shifting to a more problem-oriented mentality. A lot of people were understandably swept up in the excitement of all that AI can do, only to find that some use cases were too risky or that those problems could be solved with traditional methods that were less costly.

Why now is the time for data leaders in financial services to address the challenges of tick data analysis — and how Snowflake can help.

As one of the most widely used libraries in the Python ecosystem, pandas helps developers analyze, load and transform data across data science, data engineering and machine learning. The flexibility and ease of use of the pandas API have driven rapid growth in popularity, with pandas being used by one in every five developers, according to the StackOverflow 2024 Developer Survey.