PinnedMachine Learning is hard. Make it easier with AeroWith no infrastructure management - deploy, manage and scale Data Science & Machine Learning workflows in a reliable and easy to implement…Feb 21, 2022Feb 21, 2022
Microservices are taking over Data Engineering: And it’s a good thingMicroservices are an infamous topic in Software, but will it be the same for Data Engineering and Machine Learning?May 10, 2022May 10, 2022
Why we’re backing MetaflowWe believe Metaflow is the optimal tool for easy implementation of complex Data Science workloads while keeping the rigour of Software…Apr 28, 2022Apr 28, 2022
There is no best Data Orchestration Platform. Part 1: From an Infrastructure PerspectiveWith this useful guide, reduce the number of platforms to evaluate when considering data orchestration platforms.Apr 25, 2022Apr 25, 2022
Published inBetterDataEngineeringPainless Production — GDELT Analysis with AeroDealing with deployment, monitoring and debugging of production workflows is a pain. Aero solves this simply by providing a using…Apr 5, 2022Apr 5, 2022
Published inBetterDataEngineeringHow quickly can you process 50GBs?— Analysing GDELT with AeroDealing with large amounts of data is normally a pain, requiring lots of optimisations. Today we show that isn't always the case, how how…Mar 17, 2022Mar 17, 2022
Published inBetterDataEngineeringFrom COVID to Politics — Analysing GDELT with AeroAero is a platform built to take responsibility for infrastructure, security and orchestration away from developers and allow them to…Mar 11, 2022Mar 11, 2022
Published inTowards Data ScienceMachine Learning doesn’t occur in a vacuum, so why develop it in one?A review of the ML/DS development ecosystem: From a Software Engineers PerspectiveApr 20, 2021Apr 20, 2021
Published inTowards Data ScienceA new contender for ETL in AWS?ETL — or Extract, Transform, Load — is a common pattern for processing incoming data. It allows efficient use of resources by bunching the…Feb 22, 20211Feb 22, 20211
