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BI

Driving Profitability through Cloud Adoption

What does it take for an architecture, engineering, or construction business to be profitable? Many look toward aggressive growth and expansion, either by geography or acquisition or both. However, growth requires significant spending on resources from new employees to acquisitions, and it takes time to see a return on your investment.

How Apps Bring Gen AI & LLMs To Life

In this conversation with Snowflake's Christian Kleinerman, Amanda Kelly, and Adrien Treuille, "Data Cloud Now" anchor Ryan Green discusses the origins of Streamlit, its exponential growth as an application development tool since being acquired by Snowflake, and the important role it is playing in the development of machine learning models across all industries. This wide-ranging conversation also explores the ways Gen AI and LLMs will transform the application development process and touches on the role the Open Source community will play in that transformation.

Gen AI And LLMs Will Transform The Enterprise

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.

Simplifying BI pipelines with Snowflake dynamic tables

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.

A Closer Look at The Next Phase of Cloudera's Hybrid Data Lakehouse

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.

Snowflake Ventures Invests in Landing AI, Boosting Visual AI in the Data Cloud

As Large Language Models are revolutionizing natural language prompts, Large Vision Models (LVMs) represent another new, exciting frontier for AI. An estimated 90% of the world’s data is unstructured, much of it in the form of visual content such as images and videos. Insights from analyzing this visual data can open up powerful new use cases that significantly boost productivity and efficiency, but enterprises need sophisticated computer vision technologies to achieve this.

Gen AI And LLMs Will Change Our Lives Profoundly

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.

Geodis | Revolutionizing Global Logistics with Data

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.

Metadata Management & Data Governance with Cloudera SDX

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.