Browsing: Data

SAP aligns fragmented commerce data structures to enable operational AI personalisation at the execution layer.Enterprise leadership routinely establishes objectives to anticipate customer requirements and deliver relevant…

out to someone on LinkedIn I’d never met, asking what he thought was the best path into data engineering, and whether certifications were even worth pursuing.…

joining a new company as a data engineer. You inherit quite a few ETL pipelines and you are responsible for maintaining them. What do you think…

a significant amount of time on data preparation for downstream tasks. Whether it involves data cleaning, handling missing values, feature engineering, data preprocessing, or post processing,…

my series on Outlier Detection. In this article, we look at working with categorical data.  Generally when performing outlier detection with tabular data, we start by…

Introduction , AI examples of data engineering revolve around one thing: fixing a pipeline. An engineer opens up Claude Code, pastes some logs, and a pull…

ETL pipeline, I thought I had a pretty good grip on what data engineering actually was. You extract data from somewhere, you clean it up, you…

If your remit is to help your organisation add AI agents to accelerate its processes, you have to start at the foundation – and that means…

Autonomous AI agents are altering the speed at which software is shipped. Unfortunately, they are also shrinking the time it takes for a mistake to become…

learning, the biggest bottleneck is almost never GPU memory or model size. It’s the handful of field samples you have access to across a vast, expensive,…