Databricks vs Snowflake in 2026: Which Platform Wins?
Databricks vs Snowflake in 2026: architecture, pricing, AI workloads, and lock-in compared, with a simple rule for choosing one or running both.
Paweł SzczepanikSEO & AI Systems Specialist
Data Engineering - Page 2
Building AI-Ready Data Infrastructure in 2026
Most AI projects fail on data, not models. A practical executive guide to building AI-ready data infrastructure in 2026 — layers, pitfalls, and a 90-day path.
Paweł SzczepanikSEO & AI Systems Specialist
Data Engineering Consulting Services: What to Expect and How to Choose a Partner
Data engineering consulting services explained: what to expect, in-house vs a partner, pricing, and how to choose. Talk to DS Stream's engineers.
ETL Process Optimization: 12 Proven Techniques (2026)
ETL process optimization: 12 proven techniques to cut pipeline cost, shorten batch windows and raise data quality, plus a 30-60-90 day plan to apply them.
Paweł SzczepanikSEO & AI Systems Specialist
Breaking the Last Barrier: Why We Are Building Full-Stack Web Apps Directly Inside Databricks
Databricks Apps lets data engineers build and deploy secure full-stack internal web apps inside the lakehouse, without the usual infrastructure friction.
"SQL is the New Regex": Cleaning Messy Data with Databricks ai_query
Replace brittle regex and manual string parsing with Databricks ai_query, using SQL and PySpark AI functions to clean and standardize messy text data.
The Orchestration Dilemma: Driving the Engine vs. Designing the Factory
Databricks Workflows or Delta Live Tables in 2026? Compare driving the engine with designing the factory, and stop hand-wiring fragile data jobs.
Stop Profiling Data Manually: How AI Can Improve Data Quality in Databricks
Manual data profiling slows the move from Bronze to Silver. Use AI-assisted rules and automated checks in Databricks to raise data quality faster.
Andrzej Gabryel
The "Shift Left" Revolution: Why Your PySpark Pipelines Need Unit Tests (and How to Do It)
Shift left on data quality: unit test PySpark pipelines with modular code, local tests and CI/CD so bugs surface before they ever reach production.
AI‑Assisted Data Engineering: How to Use GenAI for Pipeline Incident Triage (Without Creating Chaos)
Using GenAI for pipeline incident triage: an operating model for faster debugging, better runbooks and lower MTTR, without new security or on-call risks.
Andrzej Gabryel
Batch vs Streaming vs Micro‑Batch in CPG and Retail: Stop Overpaying for ‘Real‑Time’ That Doesn’t Deliver ROI
Real-time data is a trade-off, not a goal. How to choose batch, streaming or micro-batch in CPG and retail, with POS, OSA and promo compliance examples.
Andrzej Gabryel
Delta Live Tables (DLT) vs dbt: Where Transformation Ends, and Platform Engineering Begins
DLT or dbt? Learn how to navigate the trade-offs between managed execution and vendor portability with a maturity checklist designed for modern data teams.