775 tutorials · free to read
A working handbook for data and software engineering.
Hands-on tutorials by Alex Merced on Apache Iceberg, the data lakehouse, pipelines, agentic AI, and the languages and tools that hold it all together.
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Latest tutorials
Page 51 of 130- 01Bringing MLflow and Data Pipelines Closer TogetherMLflow 3 extends observability from classic ML experiments to GenAI tracing and data pipeline lineage. Learn how to connect data quality monitoring with model performance tracking.Data EngineeringMay 24, 2026
- 02Modern Feature Stores Beyond Batch PipelinesFeature stores like Feast now support streaming feature views from Kafka and Kinesis alongside batch pipelines. Learn how to build real-time features that maintain training-serving consistency.Data LakehouseMay 24, 2026
- 03OpenLineage as the Spine of Data ObservabilityOpenLineage provides a standard API for collecting pipeline lineage across Airflow, Spark, Flink, and dbt. Learn how it powers blast radius analysis and incident triage.Data LakehouseMay 24, 2026
- 04When Paimon Beats Iceberg for Mutable StreamsApache Paimon uses LSM-Tree storage for native CDC upserts without restart. Learn when Paimon outperforms Iceberg for high-churn mutable streaming workloads.Apache IcebergMay 24, 2026
- 05Policy as Code for Lakehouse GovernanceOPA, ABAC, row filters, and column masks make lakehouse governance programmable and scalable. Learn how Databricks, Snowflake Horizon, and BigQuery implement policy-as-code.Data LakehouseMay 24, 2026
- 06Why Semantic Layers Make Enterprise Text-to-SQL SaferText-to-SQL accuracy jumps from 40% to 85-95% when grounded in a semantic layer. Learn how Dremio, Snowflake Cortex Analyst, and dbt Semantic Layer improve AI analytics reliability.Data LakehouseMay 24, 2026