Generic industry data models do have a place, but they serve as a kick-start to the modeling process, not the destination. Consider an address; organizations may break address components apart in ...

I'll explore data-related challenges, the increasing importance of a robust data strategy and considerations for businesses ...

In the evolving world of data architecture and analytics, Gopala Krishna Subraya Pai stands out as a thought leader whose ...

Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural ...

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

Why normalizing your clinical and claims data into standard terminologies is critical to supporting forward-thinking initiatives such as big data analytics, population health management and semantic ...

Data modeling has always been a task that seems positioned in the middle of a white-water rapids with a paddle but no canoe. On one side of the data modeling rapids are the raging agilists who are ...

Alexandra Twin has 15+ years of experience as an editor and writer, covering financial news for public and private companies. Investopedia / Zoe Hansen Overfitting occurs when a model is too closely ...