Cake for Analytics

Overview

Before you train a model or deploy a pipeline, you need to understand your data and catch issues before they create downstream problems. Analytics is the first line of defense in any AI workflow, helping teams identify anomalies, visualize trends, and evaluate model inputs at scale.

Cake integrates tools like Superset, Autoviz, and Spark into your AI pipelines—so you can explore datasets, visualize distributions, track edge cases, and debug feature behavior in context. Run one-off analyses in notebooks, automate reporting in workflows, or scale computations across distributed clusters, all without switching platforms.

With Cake’s composable architecture, you don’t need to choose between notebooks, dashboards, or pipeline-native reports; they all live in one portable stack. Whether you’re running in staging or prod, across AWS, GCP, Azure, or on-prem, your analytics tools stay consistent, scalable, and infrastructure-neutral.

Key benefits

• Accelerate insight delivery: Go from raw data to decision-ready visuals, histograms, and reports without waiting on external BI tools. 
  
  
• Use the best open-source tools: Use familiar tools like Superset and Autoviz without being tied to a proprietary stack.
  
  
• Analyze anywhere: Run consistently across clouds and environments, with no platform lock-in.