Analytics environment with managed Spark, Jupyter notebooks, automated exploratory analysis, ML pipelines, and interactive dashboards — from raw data to production insight.
Analytics Stack
Pre-configured analytics environments with GPU-backed compute and managed infrastructure.
JupyterLab with GPU kernels, collaborative editing, and version-controlled notebooks.
Auto-scaling Spark clusters with Delta Lake, structured streaming, and MLlib.
AI-driven exploratory analysis: distributions, correlations, anomalies, and data quality.
Interactive visualization with Plotly, Streamlit, and embedded BI components.
End-to-end pipelines: feature engineering, model training, evaluation, and deployment.
Discoverable datasets with lineage tracking, quality scoring, and governance metadata.
Workflow
From intent to verified engineering artifact.