Data Engineering
Data engineering is the foundation of modern data-driven organizations. It involves designing, building, and maintaining the systems and infrastructure that allow for the collection, storage, processing, and analysis of data at scale.
ETL Pipelines
Data Warehousing
Big Data
Data Lakes
Data Modeling
Popular Articles
Modern Data Stack: Components and Best Practices
An overview of the essential components in today's data stack and how to implement them effectively.
Read More
May 11, 2023
Building Scalable Data Pipelines with Apache Airflow
Learn how to design and implement robust data pipelines using this popular workflow management platform.
Read More
April 28, 2023
Data Governance for Modern Data Platforms
Implementing effective data governance in decentralized data architectures.
Read More
April 15, 2023
Data Warehousing vs. Data Lakes: When to Use Each
Understanding the strengths and use cases for these two fundamental data storage approaches.
Read More
March 30, 2023
Data Engineering Tools
Airflow
Snowflake
Spark
dbt
Quick Facts
- Data engineers enable analytics and AI by making data accessible and reliable.
- Modern data stacks use cloud-native, scalable tools.
- ETL and ELT pipelines automate data movement and transformation.
- Data governance ensures quality, compliance, and trust.
Key Concepts
ETL
ELT
Data Lakehouse
DataOps