Discover how Cloudera brings data anywhere, helps channel partners become trusted experts for their accounts, drive business growth, and accelerate their customers’ AI journey.
If you've just enabled Kai in your Keboola project, you might be wondering: "Okay, now what?" This guide walks you through your first conversation with Kai, following the same steps I demonstrate in my introduction video.
Many financial institutions are finding that improving education isn't enough to solve their data management struggles. It’s time to move from “proof of concept” to “intelligence orchestration.” The gap between AI experimentation and real-world ROI is widening. In this video, we break down why a robust, proprietary data foundation is the only way to scale AI safely and effectively. We explore why financial services must move beyond public data and focus on unique, high-value data assets to create a true competitive advantage.
As telecom operators invest billions in next-generation networks, many are racing to deploy AI to cut costs and unlock new revenue. But beneath the push for automation and smarter infrastructure lies the deeper challenge of rethinking how connectivity itself should be trusted.
Every business decision relies on data—and bad data leads to bad decisions. ETL testing validates that your data extraction, transformation, and loading processes deliver accurate, complete, and consistent information to your analytics platforms. In 2026, the stakes have never been higher for organizations struggling with manual data validation that automated testing could eliminate.
Despite widespread awareness of data governance principles, 61% of organizations still list data quality as a top challenge. The gap between knowing what enterprise data management (EDM) requires and actually executing it continues to widen as data volumes explode and AI initiatives demand cleaner, more reliable information.
One year ago, we introduced Analyst Studio, ThoughtSpot’s unified workspace for preparing and managing AI-ready data, with a vision: to transform analysts from report generators into business catalysts. SQL, Python, and visual analysis finally worked together in one workspace, letting data teams move seamlessly between ad-hoc queries and advanced modeling, all while preparing data for the AI revolution we knew was coming.
@MDauditSoftware did it by swapping "data babysitting" for ThoughtSpot. After 6 years, they’ve unlocked a "shadow workforce" that handles the tech so the team can focus on growth. The Result: Total operational independence Zero maintenance, more innovation Strategic agility at scale Stop DIY-ing your AI.
Stop falling into "Manual Toggle Fatigue" and start mastering dynamic Liveboard control. In this technical walkthrough, we explore how to leverage Parameters paired with Custom Formulas to update granularity across an entire suite of visuals with a single selection.
Customers don’t buy software because they feel loved. They buy it because the product works, solves a real problem, meets security, scalability, and reliability requirements, and fits their budget. No amount of empathy or friendliness can compensate for missing features or poor performance. So at first glance, it’s easy to assume that great products alone win customer loyalty. But once the contract is signed and the product is in use, the rules change.