ETL / ELT systems
Pipelines extract, transform, and load data across systems while enforcing schema, quality, and timing constraints.
What It Is
Data Engineering is the design and construction of systems for collecting, storing, and processing data. On this site, it matters because it transfers across technical, operational, and venture work instead of staying trapped in one narrow context.
Learn more: https://en.wikipedia.org/wiki/Data_engineering
Amazon Kinesis
Amazon Kinesis is a real-time data streaming platform for ingestion and processing.
Amazon Redshift
Amazon Redshift is a cloud data warehouse for large-scale analytics.
Data Engineering and Big Data
Projects building data pipelines, warehouses, lakes, and large-scale analytics infrastructure.
Data modeling systems
Abstract representations of entities and relationships are structured for efficient storage, querying, and interpretation.
Data Product Systems
Pipelines and structures turn raw data into packaged, sellable, and repeatable products with defined schemas and use cases.
Great Data Lake
A data brokerage and value-add business focused on transforming large raw datasets into usable commercial products.
Redis
Redis is an in-memory data store for caching and real-time systems.
SQL
SQL is a language for querying and managing relational databases.
Python
Python is a programming language for automation, data, and backend systems.