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How Yellowfin Provides True Data Storytelling

Being able to create and share insightful data-led stories to support your dashboards and reports is a critical capability in today’s modern workplace. You want your data to be accessible for more people, and ensure everyone gets value from your investments. Data storytelling tools bring valuable context to the ‘why’ behind the results, while inspiring your audience to care about and act on insights.

Cloudera and Snowflake Partner to Deliver the Most Comprehensive Open Data Lakehouse

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI. One of the most important innovations in data management is open table formats, specifically Apache Iceberg, which fundamentally transforms the way data teams manage operational metadata in the data lake.

Leveraging Snowflake And AI To Create Personalized Customer Experiences At Scale

In this episode of the "Data Cloud Podcast", Bill Stratton, Global Head of Media, Entertainment & Advertising at Snowflake, sits down with Ravi Kandikonda, Sr. VP of Marketing at Zillow. Ravi shares his experiences and insights on modern software development, talks about how his academic background prepared him for modern marketing, and what Zillow is doing to approach personalization at scale.

Qlik Anonymous Access - SaaS in 60

Qlik Anonymous Access is an exclusive, new capability that enables organizations to share analytics insights with a public audience easily. It leverages Qlik Cloud’s secure and scalable platform, allowing you to embed Qlik Sense apps, dashboards, and visualizations into websites or third-party applications using shareable links or our new Qlik Embed APIs. With Anonymous Access, no login credentials are required, simplifying engagement with embedded analytics.

The Evolution of LLMOps: Adapting MLOps for GenAI

In recent years, machine learning operations (MLOps) have become the standard practice for developing, deploying, and managing machine learning models. MLOps standardizes processes and workflows for faster, scalable, and risk-free model deployment, centralizing model management, automating CI/CD for deployment, providing continuous monitoring, and ensuring governance and release best practices.

Databricks + Unravel: Achieve Speed and Scale on the Lakehouse

Companies are under pressure to deliver faster innovation, enabled by cloud-based data analytics and AI. In order to deliver faster business value, data teams are looking to achieve speed and scale through data and AI pipeline performance and efficiency. A recent MIT Technology Review Insights report finds that 72% of technology leaders agree that data challenges are the most likely factor to jeopardize AI/ML goals.