Blogs
Insights, perspectives, and deep-dives on AI, data engineering, cloud architecture, and the future of intelligent enterprise systems
Articles & Insights
Sharing knowledge built from 20+ years of enterprise technology experience and applied AI research
Synthetic Data Generation: Solving Retail Demand Forecasting at Scale
How generative AI can close the gap between limited historical data and robust demand forecasting models — lessons from an IEEE published research project.
Read Research Paper →Event-Driven Architecture for Real-Time Retail Analytics
Designing streaming data architectures with Kafka, Pub/Sub, and Dataflow to deliver sub-second business insights across enterprise retail networks.
Read Research Paper →Building Trustworthy AI for Retail Pricing: Principles & Architecture
What does it mean to build truly trustworthy AI for pricing decisions? Exploring explainability, fairness, and auditability in cloud-native AI systems.
Read Research Paper →Agentic AI in Production: How Multi-Agent Frameworks Are Transforming Engineering
A practitioner's view on deploying multi-agent AI systems that autonomously generate, review, and validate enterprise code — reducing modernization costs dramatically.
Coming SoonMigrating Enterprise Data from Hadoop to GCP: Lessons from Three Production Migrations
The architectural decisions, trade-offs, and hard-won lessons from migrating three major Hadoop clusters and their datasets to Google Cloud Platform at Macy's.
Coming SoonAI-Driven Predictive Observability: Moving from Reactive to Proactive Data Pipeline Monitoring
How we built predictive observability dashboards using AI to detect data quality issues before they impact business decisions — a deep dive into our GCP implementation.
Coming SoonWriting Blogs & Knowledge Sharing
Thought leadership, technical writing, and industry insights that bridge data, AI, and observability.
DataVersity Blog
This blog explores why observability for business intelligence and observability for artificial intelligence require different approaches. It draws on practical lessons from large-scale analytics, cloud data platforms, and AI system monitoring.
Read the full article on DataVersity: Why Observability for BI is Not Observability for AI.
HackerNoon Blog
This story argues that AI's core challenge is not data, but decision-making. It explains how decision intelligence, automation, and operational alignment are the missing links for enterprise AI success.
Read the full article on HackerNoon: AI Doesn't Have a Data Problem—It Has a Decision Problem.
Dev.to Blog
A deep retail observability article that shows how AI-powered predictive monitoring helps data pipelines catch silent corruption before business users notice.
Read the full article on Dev.to: Beyond Monitoring: Building AI-Powered Predictive Observability for Retail Data Pipelines.
Dev.to Blog
Practical strategies for optimizing BigQuery costs in production, with proven approaches to reduce spend while keeping analytics fast and reliable.
Read the full article on Dev.to: How to Optimize BigQuery Costs (Real Techniques That Work).
Medium Blog
Near real-time streaming ingestion into BigQuery without Dataflow and Pub/Sub, with a practical architecture for low-overhead Kafka + Flume + GCS pipelines.
Read the full article on Medium: Near Real-Time Streaming Ingestion into BigQuery without Dataflow and Pub/Sub.
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