My book, Practical DataOps: Delivering Agile Data Science at Scale, is available to buy at Amazon (UK), Amazon.com and other retailers. About the book Gain a practical introduction to DataOps, a new discipline for…

Advances in machine learning algorithms and an explosion in software tools have ushered in a transformative period for business, science and medicine. Machine learning is now one of the hottest topics in the World. However, there is far more to successful implementation of Machine Learning than just creating great models. Algorithms are just the tip of the iceberg when it comes to creating business and customer value from data.

I spoke to CloudPro recently about Moneysupermarket’s migration to the cloud and our use of Google Cloud Storage. Read the article here.

By using Google Kubernetes Engine (GKE), price comparison site MoneySupermarket.com has been able to parallelise its data pipeline. This is part of a wider deployment of analytics services on Google’s public cloud. It recently moved to Google Cloud Platform (GCP), which has enabled it to take advantage of the analytics services built into GCP.

Paul Laughlin of DataInsightLeaders.com has written a review of my book, Practical DataOps: Delivering Agile Data Science at Scale. Find out why he recommends the book to all data leaders…

On Monday, we welcomed Harvinder Atwal, Head of Data Strategy and Advanced Analytics at Moneysupermarket.com, who spoke to us about Machine Learning, challenges, solutions and experiences. I don’t think Moneysupermarket needs much of an introduction, but for those who are a little confused: as Harvinder said, they’re “not the meerkat guys, so don’t call asking whether Oleg or Alexander are on their way!” You will, however, recognise Moneysupermarket.com from their memorable adverts, such as the ones below;

I recently spoke to Cliff Saran, Managing Editor of Computer Weekly on the importance of data in combatting coronavirus and DataOps as a way to build better data pipelines. Read…

A recent Forrester report found that only 22% of companies see a return on investment (ROI) from data science. Given the tantalising opportunities that data science, artificial intelligence (AI) and advanced analytics promise business, why do most initiatives fail?

I had a great time discussing the key principles of DataOps with Catherine King from Business of Data. You can hear it here: https://www.business-of-data.com/podcasts/harvinder-atwal-moneysupermarket-dataops