Accelerating and Scaling AI Deployments Across Hybrid Environments - MLOps Live #40 with Safaricom

Safaricom, one of the most AI-mature mobile operators, delivers predictive modeling and hyper-personalized financial services to millions of users. But operational challenges were slowing down deployments—limiting their ability to scale and act in real time. In this session, Safaricom’s AI team shares how they: Watch now to learn how they overcame bottlenecks, scaled faster, and unlocked real-time impact at massive scale with the Iguazio technology.

Hidden Costs and Insights in Embedded Analytics Pricing

Key takeaways of embedded BI pricing: TL;DR Interested in pricing for Yellowfin? Request a quote. We’ve all been there: you’ve found the perfect solution for your product, but then you get to the pricing page and see a cost or pricing model that makes your jaw drop. That’s the "sticker shock" we want to help you avoid when buying embedded analytics. While the value of embedding BI is clear, not all pricing models are created equal.

Effortless Table Management with Qlik's Adaptive Iceberg Optimizer: Boost Performance, Cut Costs

Boost query performance by more than 2.5X and reduce storage costs by 50% compared to self-tuned Hive tables, without lifting a finger. Many data teams still need to manually develop and schedule custom tasks to maintain each and every table in their lakehouse, leading to inconsistent query performance and runaway costs.

How To Make Sense of Enterprise-Level Data With Google Cloud's Vertex AI and BigQuery

As an application developer integrating analytics into your application, your users expect a scalable, flexible solution that adapts to changing business needs. While organizations strive to capitalize on new AI tools, they’re also still wrestling with big data: massive, fast-moving datasets that traditional tools can’t handle easily.

Best Practices to Develop, Deploy, and Manage Gen AI Copilots

Generative AI copilots are moving from experimental tools to core enterprise solutions. But too often, organizations rush into development, only to discover adoption stalls because the copilot doesn’t solve a specific user problem, lacks trust safeguards, or can’t scale reliably. This guide lays out best practices across the entire lifecycle, from planning and building, to deployment, monitoring, and long-term maintenance.

AI Inside Snowflake: Practical Applications for Data Teams

Snowflake is rapidly evolving into an AI-powered data platform, enabling organizations to go beyond traditional analytics and bring intelligence directly into their data workflows. In this session, Vivek Sunny will share practical insights from his hands-on experience implementing AI-driven solutions on Snowflake—bridging data engineering with AI to unlock business value.