
Why Is Data Engineering Important?
Data engineering is the central foundation for any advanced data project. Companies produce vast amounts of raw data, but it often lacks consistency in structure and formatting.
Data engineering takes these different sources and creates a consistent pipeline to enable the likes of AI, Data Science and Data Visualisation solutions.
Pipeline Automation
Big Data can’t be handled manually. Automation is needed for the most efficient and optimised practices. An optimised pipeline can Extract, Transform and Load (ETL) all of your data, seamlessly moving from raw, unconnected data sets to formatted and structured data that’s automatically updated for real-time results.
ETL

Machine Learning
Big Data
Data Visualisation
Data Science
Dashboards
Analytics
What Can Data Engineering Do For You?
Sources
Acquisition
Format Data
Storage
Data Engineering & The Cloud
An automated process needs scalable servers able to spin up production when large volumes of data are processed, but don’t sit idle while not in use. Cloud infrastructure allows exactly that.

How To Get Started With Data Engineering?