Dataengineering

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Iurii Rogulia

Jun 18

JSON vs YAML vs TOML vs CSV vs Protobuf: Developer's Guide

#typescript #python #developertools #dataengineering

13 min read

DataDriven

Jun 18

Why ClickHouse Merges and Mutations Are Difficult to Track in Production

#clickhouse #database #dataengineering #observability

3 min read

Akhila Chanubala

Jun 17

Building a Public Clinical Trial Data Quality Observatory with Python

#python #dataengineering #opensource #healthtech

3 min read

Anusha Mukka

Jul 20

Data Is the Real Model: Governance, Lineage, and Provenance

#ai #dataengineering #security #machinelearning

5 min read

Adrian Galik

Jul 21

Why I Built DagSmith: Bringing a Visual Drag-and-Drop Editor straight into Apache Airflow 3

#python #airflow #dataengineering #opensource

3 min read

Alex Natskovich

Jun 17

Choosing a Healthcare Data Management Service Provider

#healthtech #dataengineering #mdm

5 min read

Wangila russell

Jul 21

Kafka Topics, Partitions, and Offsets Explained: The Concepts Every Beginner Confuses

#beginners #dataengineering #streaming #tutorial

3 min read

Fritz Larco

Jun 17

Effortless Data Migration: How to Export from PostgreSQL and Load into S3 as Parquet with Sling

#postgres #s3 #parquet #dataengineering

8 min read

aravind_akay

Jun 21

Sharding in a nutshell

#systemdesign #dataengineering #database #webdev

3 min read

Vaibhav

Jul 21

Building a Document Intelligence Pipeline (Or: 80% of Your Data Is in PDFs)

#dataengineering #ai #python #architecture

3 min read

Marco Marques

Jun 21

I'm opening ContractForge — define data ingestion intent once, run it natively anywhere

#dataengineering #datacontract #opensource #ai

2 min read

wwr0ngn4m3

Jul 21

Zero-Downtime MariaDB PostgreSQL Migration: Why the Usual Tools Fell Short, and How Debezium CDC Solved It

#database #dataengineering #devops #postgres

9 min read

Kanishga Subramani

Jun 17

Day 20 of 100 Days of ClickHouse® - Introduction to Materialized Views

#clickhouse #devops #database #dataengineering

2 min read

Kanishga Subramani

Jun 21

Day 29 of 100 Days of ClickHouse® - Understanding Distributed Tables

#analytics #clickhouse #database #dataengineering

4 min read

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DEV Community

#dataengineering

JSON vs YAML vs TOML vs CSV vs Protobuf: Developer's Guide

Top 12 Pipeline Architecture Interview Questions, With Answers

Why ClickHouse Merges and Mutations Are Difficult to Track in Production

Building a Public Clinical Trial Data Quality Observatory with Python

Data Is the Real Model: Governance, Lineage, and Provenance

Why I Built DagSmith: Bringing a Visual Drag-and-Drop Editor straight into Apache Airflow 3

Choosing a Healthcare Data Management Service Provider

Kafka Topics, Partitions, and Offsets Explained: The Concepts Every Beginner Confuses

Effortless Data Migration: How to Export from PostgreSQL and Load into S3 as Parquet with Sling

Sharding in a nutshell

Building a Document Intelligence Pipeline (Or: 80% of Your Data Is in PDFs)

I'm opening ContractForge — define data ingestion intent once, run it natively anywhere

Zero-Downtime MariaDB PostgreSQL Migration: Why the Usual Tools Fell Short, and How Debezium CDC Solved It

Day 20 of 100 Days of ClickHouse® - Introduction to Materialized Views

Day 29 of 100 Days of ClickHouse® - Understanding Distributed Tables