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Some companies have created that unfair advantage by unlocking data’s hidden treasures, or by leveraging a powerful ecosystem, or by overcoming adversity, or through other great means like a unique company culture. Another great way is driving excellence in partner engagements to unlock value quicker than your competitors. So, what are the key ingredients for that particular recipe?
Some 70% of organizations are actively exploring or implementing large language model (LLM) use cases, but fewer than a third of generative AI experiments have made it into production. A common hurdle? The inability to access and leverage the data crucial for running AI applications effectively. Snowflake’s Accelerate 2025 virtual events dive into the challenges and myriad opportunities offered by AI.
We recently had the pleasure of chatting with Dots Oyebolu on the podcast, where we talked about marketing metrics that matter (LTV, ACV, revenue), his two-dimensional marketing framework of combining Go-to-Market Motions (inbound, outbound, partnerships, community, PLG) with Marketing Approaches (brand awareness, demand generation, performance marketing), and why all three marketing approaches need to work together.
In this demo, we’ll show you how to create a custom Data Metric Function (DMF), associate it with your tables for continuous data quality monitoring, and query the results from a centralized table. Watch to learn how built-in monitoring helps you track critical data objects, identify quality issues, and take quick action to ensure reliable, high-integrity data across your organization.
Many organizations run Apache Kafka clusters in private Azure networks to meet stringent security, compliance, and operational requirements. However, securely replicating data across clusters without exposing traffic to the public internet has traditionally been complex, requiring self-managed mirroring solutions with significant operational overhead.
This demo presents a Telco-focused GenAI agent co-pilot in action, providing assistance to a representative during a live conversation with a customer. The co-pilot recommends a highly personalized upsell opportunity in the process.
Artificial Intelligence (AI) is transforming the way businesses manage, process, and analyze data. AI Data Management involves the use of machine learning (ML), automation, and intelligent data pipelines to enhance data storage, governance, integration, and security. As organizations deal with ever-growing datasets, AI-driven data management solutions ensure efficiency, scalability, and accuracy.