Calculate running totals, rankings, and moving averages efficiently with SQL window functions.
Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Data Quality for AI: Ensuring High-Quality Training Data
Data quality determines AI model performance. After managing data quality for 100+ AI projects, I’ve learned what matters. Here’s the complete guide to ensuring high-quality training data. Figure 1: Data Quality Framework Why Data Quality Matters Data quality directly impacts model performance: Accuracy: Poor data leads to poor predictions Bias: Biased data creates biased models… Continue reading
Production Model Deployment Patterns: From REST APIs to Kubernetes Orchestration in Python
After 20 years in this industry, I’ve seen Production Model Deployment Patterns evolve from [past state] to [current state]. The fundamentals haven’t changed, but the implementation details have. Let me share what I’ve learned. The Fundamentals Understanding the fundamentals is crucial. Many people skip this and jump to implementation, which leads to problems later. How… Continue reading
Mastering LangChain: The Complete Getting Started Guide to Building Production LLM Applications
Introduction: LangChain has emerged as the de facto standard framework for building applications powered by large language models. Originally released in October 2022, it has grown from a simple prompt chaining library into a comprehensive ecosystem that includes LangChain Core, LangChain Community, LangGraph, and LangSmith. With over 90,000 GitHub stars and adoption by thousands of… Continue reading
Tips and Tricks – Use CQRS for Complex Domain Logic
Separate read and write operations for better scalability and simpler code.
Tips and Tricks – Use AWS Lambda Layers for Shared Dependencies
Share common code and dependencies across Lambda functions to reduce deployment size.
Tips and Tricks – Use Terraform Modules for Reusable Infrastructure
Create reusable infrastructure components with Terraform modules for consistency and DRY code.
BigQuery Unleashed: Building Enterprise Data Warehouses That Scale to Petabytes
Introduction: BigQuery stands as Google Cloud’s crown jewel—a serverless, petabyte-scale data warehouse that has fundamentally changed how enterprises approach analytics. This comprehensive guide explores BigQuery’s enterprise capabilities, from columnar storage and slot-based execution to advanced features like BigQuery ML, BI Engine, and real-time streaming. After architecting data platforms across all major cloud providers, I’ve found… Continue reading
ETL for Vector Embeddings: Preparing Data for RAG
Preparing data for RAG requires specialized ETL pipelines. After building pipelines for 50+ RAG systems, I’ve learned what works. Here’s the complete guide to ETL for vector embeddings.
Feature Engineering at Scale: Building Production Feature Stores and Real-Time Serving Pipelines
Introduction: Feature engineering remains the most impactful activity in machine learning, often determining model success more than algorithm selection. This comprehensive guide explores production feature engineering patterns, from feature stores and versioning to automated feature generation and real-time feature serving. After building feature platforms across multiple organizations, I’ve learned that success depends on treating features… Continue reading