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Snowflake's Mona Attariyan, Director of Engineering, leads this conversation with Snowflake's Sunny Bedi, CIO and CDO, and Jennifer Belissent, Principal Data Strategist, about the impact Gen AI and LLMs will have on enterprises. Topics covered range from the impact on employee productivity, the personalization of the customer experience, the opportunities for data monetization. and more.
Managing complex data pipelines is a major challenge for data-driven organizations looking to accelerate analytics initiatives. While AI-powered, self-service BI platforms like ThoughtSpot can fully operationalize insights at scale by delivering visual data exploration and discovery, it still requires robust underlying data management. Now, that’s changing. Snowflake's new dynamic tables feature redefines how BI and analytics teams approach data transformation pipelines.
Artificial Intelligence (AI) is primed to reshape the way just about every business operates. Cloudera research projected that more than one third (36%) of organizations in the U.S. are in the early stages of exploring the potential for AI implementation. But even with its rise, AI is still a struggle for some enterprises. AI, and any analytics for that matter, are only as good as the data upon which they are based. And that’s where the rub is.
Because human-machine interaction using natural language is now possible with large language models (LLMs), more data teams and developers can bring AI to their daily workflows.
How will Gen AI and LLMs impact the nature of people's jobs and worker productivity? "Data Cloud Now" anchor Ryan Green kicked off the Data and AI Predictions 2024 event in January by discussing that topic with Snowflake's CEO Sridhar Ramaswamy and Mona Attariyan, Director of Engineering. The conversation also covers the potential for AI to generate misinformation and the need to establish ethical guardrails for the technology.
Explore how Geodis, a global logistics powerhouse, stays ahead of the curve in an ever-changing industry. Witness how they leverage real-time data and innovative solutions from Cloudera to streamline operations, enhance visibility, and exceed customer expectations, propelling their business forward in a world that never stops moving.
Understanding how to get data into your Kafka cluster is the first step to real-time streaming data. Producer has entered the chat. Watch this video to find out all you need to know about how a Kafka producer helps your data flow into the future.
In this article, we will walk you through the process of implementing fine grained access control for the data governance framework within the Cloudera platform. This will allow a data office to implement access policies over metadata management assets like tags or classifications, business glossaries, and data catalog entities, laying the foundation for comprehensive data access control.