Posts - Page 40
All the articles I've posted, page 40.
- 3 MIN READ•Jul 22, 2025
The Basics of Compaction – Bin Packing Your Data for Efficiency
Learn how standard compaction works in Apache Iceberg and why bin packing your data files is essential for maintaining query performance and cost efficiency.
Apache IcebergData OptimizationTable Maintenance - 3 MIN READ•Jul 15, 2025
The Cost of Neglect – How Apache Iceberg Tables Degrade Without Optimization
Learn how Apache Iceberg tables can degrade over time without optimization and what issues this causes for performance, cost, and governance.
Apache IcebergData LakehouseOptimization - 6 MIN READ•Jul 3, 2025
How to Discover or Organize Lakehouse & Apache Iceberg Meetups
Guide on How to Be Part of the Lakehouse Community
Data LakehouseData Engineering - 10 MIN READ•Jun 23, 2025
What is an API? And Why Data Architecture Depends on Them
What an API is, how SOAP, REST, RPC, and GraphQL differ, and why data architecture runs on APIs like S3, JDBC, ADBC, Hive Metastore, Glue, and Iceberg REST.
Data LakehouseData Engineering - 7 MIN READ•Jun 18, 2025
Decoding AWS EC2 Instance Type Names
How to read AWS EC2 instance names like c6g.large and r5d.4xlarge: what the family letter, generation number, suffixes like g and d, and size each mean.
DevOpsCloud - 4 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | What is Data Engineering?
What data engineers do, how raw data moves through a pipeline to become usable, how the role differs from data science, and how the data stack evolved.
Data EngineeringDatabasesData Lakes - 4 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | Understanding Data Sources and Ingestion
Common data sources, batch versus streaming ingestion, structured, semi-structured, and unstructured data, and how to design reliable ingestion pipelines.
Data EngineeringDatabasesData Lakes - 4 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | ETL vs ELT – Understanding Data Pipelines
The difference between ETL and ELT pipelines, why ELT took off with cloud warehouses, and when transforming data before loading it is still the better choice.
Data EngineeringDatabasesData Lakes - 5 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | Batch Processing Fundamentals
What batch processing is, how batch jobs run under the hood, the tools that build and schedule them, their limits, and where batch still beats streaming.
Data EngineeringDatabasesData Lakes - 5 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | Streaming Data Fundamentals
What streaming data is, how producers, message brokers, and stream processors work together, real-time use cases, and the challenges of streaming pipelines.
Data EngineeringDatabasesData Lakes - 5 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | Data Modeling Basics
Data modeling basics: OLTP versus OLAP systems, normalization and denormalization, star and snowflake schemas, and how to design models that can grow.
Data EngineeringDatabasesData Lakes - 5 MIN READ•May 2, 2025
Introduction to Data Engineering Concepts | Data Warehousing Fundamentals
What a data warehouse is and how it differs from an operational database: architecture, columnar storage, partitioning and clustering, and load patterns.
Data EngineeringDatabasesData Lakes