Implement semantic search using text embeddings for more relevant results than keyword matching.
Read more →Tag: ETL
Tips and Tricks – Use dbt for Maintainable Data Transformations
Build modular, tested, documented data transformations with dbt.
Read more →Tips and Tricks – Partition Large Tables for Query Performance
Use table partitioning to dramatically speed up queries on large datasets.
Read more →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 […]
Read more →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.
Read more →Spark Isn’t Magic: What Twenty Years of Data Engineering Taught Me About Distributed Processing
🎓 AUTHORITY NOTE Drawing from 20+ years of data engineering experience across Fortune 500 enterprises, having architected and optimized Spark deployments processing petabytes of data daily. This represents production-tested knowledge, not theoretical understanding. Executive Summary Every few years, a technology emerges that fundamentally changes how we think about data processing. MapReduce did it in 2004. […]
Read more →