🚀 Comprehensive Data Engineering Documentation Resources 📚

This document provides links to official documentation for various technologies and platforms commonly used by Data Engineers.

1. ☁️ Cloud Platforms

AWS

• 📗 AWS Data Engineering Docs
• 🔄 AWS Glue
• 🗄️ AWS Redshift
• 📊 AWS Kinesis
• 🐘 AWS EMR

Google Cloud (GCP)

• 📘 Google Cloud Data Engineering
• 🔍 BigQuery
• 🌊 Dataflow (Apache Beam)
• ✨ Dataproc (Spark)
• 📡 Pub/Sub

Microsoft Azure

• 📙 Azure Data Engineering
• 🏭 Azure Data Factory
• ⚡ Azure Databricks
• 🔄 Azure Synapse Analytics
• 📈 Azure Stream Analytics

2. 🐘 Big Data & Processing Frameworks

Apache Spark

• 🔥 Spark Official Docs
• 🐍 PySpark API

Apache Kafka

• 📫 Kafka Documentation

Apache Flink

• 🌊 Flink Docs

Apache Beam

• 🔦 Beam Documentation

Apache Hadoop

• 🐘 Hadoop Docs

Apache Airflow

• 🔄 Airflow Docs

3. 🗄️ Databases & Data Warehousing

SQL & NoSQL Databases

• 🐘 PostgreSQL
• 🐬 MySQL
• 🍃 MongoDB
• 💎 Cassandra

Data Warehouses

• ❄️ Snowflake
• 🔍 BigQuery
• 🔴 Redshift

4. 🔄 Data Pipelines & ETL Tools

ETL & Workflow Tools

• 🔄 Apache NiFi
• 🧩 Talend
• 📊 Informatica
• 🧱 dbt (Data Build Tool)

5. 💻 Programming & Querying

Python for Data Engineering

• 🐍 Python Official Docs
• 🐼 Pandas
• 🏹 PyArrow

6. 🛠️ DevOps & Orchestration

Docker & Kubernetes

• 🐳 Docker Docs
• ☸️ Kubernetes Docs

CI/CD

• 🔄 GitHub Actions
• 🦊 GitLab CI/CD

7. 📊 Monitoring & Logging

Monitoring Tools

• 📈 Prometheus
• 📊 Grafana
• 🔍 ELK Stack (Elasticsearch, Logstash, Kibana)