Data Engineering
Artificial Intelligence
dbt semantic models in 2026: how to build a metrics layer that AI agents can actually trust
dbt semantic models: the metrics layer AI agents can actually trust.
10 min of reading
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Data Engineering
dbt Mesh in practice: how to scale data modeling across multiple teams and business units
Scale data modeling by domain with dbt Mesh across teams.
9 min of reading
Data Engineering
Data Analytics
How to integrate Apache Airflow with OpenLineage for full data traceability
Wire OpenLineage into Airflow for automatic, end-to-end data lineage.
8 min of reading
Data Engineering
Artificial Intelligence
Databricks Genie Code in 2026: a hands-on guide to AI-assisted data engineering and SQL generation
A hands-on guide to Databricks Genie Code for SQL and data engineering.
8 min of reading
Data Engineering
Data Analytics
BigQuery cost optimization: how to implement partitioning, clustering, and BI Engine
Cut your BigQuery bill with partitioning, clustering, and BI Engine.
9 min of reading
Data Engineering
Artificial Intelligence
AWS vs Azure vs Google Cloud for data and AI in 2026: a technical decision guide
How to choose AWS, Azure or Google Cloud for data and AI in 2026.
9 min of reading
Artificial Intelligence
Data Engineering
Snowflake Cortex: how to implement generative AI directly in your SQL tables
Run generative AI inside your SQL tables with Snowflake Cortex.
7 min of reading
Artificial Intelligence
Data Engineering
OpenTelemetry in 2026: how to add observability to AI agent systems
Instrument AI agents with OpenTelemetry: tracing, metrics and logs.
9 min of reading
Data Engineering
Data Analytics
Data Mesh vs Data Lakehouse in 2026: an honest architectural comparison for modern data teams
Data Mesh vs Data Lakehouse: the difference and when to use each.
8 min of reading
