Learn from Google’s Data Engineers: Dimensional Data Modeling is Dead
My first day at Google was in 2019, and one of my biggest surprises was that I didn’t find any dimensional data marts. I was
My first day at Google was in 2019, and one of my biggest surprises was that I didn’t find any dimensional data marts. I was
A guide to what your data science and AI experts can be expected to contribute as companies grapple with ever-increasing amounts of data. Just about
Companies growing at a fast pace enjoy two unique advantages simultaneously. They are able to utilize small but mighty teams with a can-do attitude and
Have you ever received a call from your bank because they suspected fraudulent activity? Most banks can automatically identify when spending patterns or locations have
As the global business landscape is increasingly digitalised, and new technologies like 5G drive the exponential expansion of the Internet of Things (IoT), the amount
Graph databases and knowledge graphs, in particular, have seen an uptick in interest among CIOs, digital transformation managers and others in enterprise circles. Some of
While AutoML started out as an automation approach to develop optimal machine learning pipelines, extensions of AutoML to Data Science embedded products can now enable
A graph database is designed around the concept of a mathematical graph. Unlike relational databases, they allow you to connect data together. This enables users
In his role as principal data scientist at consulting firm Booz Allen Hamilton Inc., Kirk Borne sees the world in terms of data connections. “Life
In this blog post, we’ll discuss the differences between row store and column store databases. Clients often ask us if they should or could be
Data lakes are centralized storage and data repositories that allow you to work with a variety of different types of data. (Photo: Rich Miller) In
Over the last decade, the increased use of unstructured and alternative data, and the ascendance of the cloud, has posed an overt challenge to the