End-to-End Data Pipelines for Machine Learning on the Cloud Post date May 20, 2026 Post author By Seshendranath Balla Post categories In data-engineering, delta-lake, end-to-end-data-pipelines, machine-learning, machine-learning-on-the-cloud, mlops, pyspark, spark
Optimizing Distributed Data Processing for ML at Scale Post date May 20, 2026 Post author By Seshendranath Balla Post categories In data-engineering, distributed-data-processing, distributed-systems, machine-learning, optimizing-distributed-data, performance-optimization, pyspark, spark
At Petabyte Scale, ML Stops Being About Models Post date May 7, 2026 Post author By Seshendranath Balla Post categories In data-engineering, data-pipelines, delta-lake, feast-integration, feature-store, ml-as-a-data-system, mlops, TensorFlow
The Architectural Limits of Data Lakes and the Rise of Lakehouses Post date May 7, 2026 Post author By Seshendranath Balla Post categories In acid-transactions, apache-hudi, data-architecture, data-governance, data-lakehouse, delta-lake, open-table-formats, schema-evolution
Why Modern Systems Are Built Around Logs, State, and Time Post date May 6, 2026 Post author By Seshendranath Balla Post categories In cdc, dataflow-modelling, distributed-systems, event-streaming, flink, kafka, stateful-applications, stream-processing
Designing Data-Driven Intelligent Systems for Customer Lifecycle Optimization Post date May 6, 2026 Post author By Seshendranath Balla Post categories In churn-prediction, customer retention, customer-lifecycle, data-driven-intelligent-system, data-pipelines, feature-engineering, mlops, uplift-modeling
How Latency, Drift, and Cost Quietly Undermine Data Pipelines Post date May 6, 2026 Post author By Seshendranath Balla Post categories In aws-cost-optimization, data-drift, data-engineering, data-observability, data-pipelines, data-quality, kafka, spark
The Cost of Correctness in “Real-Time” Systems Like Kafka and Spark Post date May 6, 2026 Post author By Seshendranath Balla Post categories In data-engineering, digital-watermarking, distributed-systems, kafka, real-time-data, spark, spark-structured-streaming, stream-processing
Designing Enterprise-Grade Offer Management Systems with Rule-Based Decision Engines Post date May 5, 2026 Post author By Seshendranath Balla Post categories In data-governance, debezium, decision-engine, enterprise-architecture, event-driven-systems, offer-management-systems, pricing-systems, resilience4j
Why More Data Doesn’t Guarantee Better Insights in Modern Data Systems Post date May 5, 2026 Post author By Seshendranath Balla Post categories In data-engineering, data-observability, data-quality, data-validation, enterprise-data-engineering, feature-selection, pipeline-reliability, sampling-bias-in-test-sets
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