Data warehouses have emerged as a viable solution for collecting, analyzing, and leveraging data. Find out if your organization needs a data warehouse.
Take an in-depth look at data platforms, why your business might need one, and tips for making an informed technology decision.
Medical search engines done right need machine learning to provide the best returns. It's an incredibly complex field with a high volume and variety of data.
For e-banking, simple surveys cannot offer enough insight into customer satisfaction to help make predictions, but machine learning can.
UAI and machine learning in banking are quietly becoming the norm thanks to the improvements in speed and accuracy gained in banking operations.
Using AI and machine learning in banking is a logical development—but how do they work exactly?
What are data lake platforms and how did they come about? What are the components of a cloud data lake? Find out in this article covering the basics!
AWS Datalake is one of the best known solutions for handling vast amounts of varied data. We look at the data lake and its architecture.
Should I build a data lake? What are the benefits and challenges of data lakes?
The future of clinical trials might very much depend on AI-based technology—specifically on machine learning.
Electronic medical records processing, compared to paper-based systems, is much more convenient—but it also brings about another huge advantage.
By standardizing nurse triage guidelines through automation, triage systems can help ease the burden on modern medical care.
