This Perspective examines single-cell RNA-seq data challenges and the need for normalization methods designed specifically for single-cell data in order to remove technical biases.

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, ...

It’s tempting just to replicate all databases in the cloud, but it’s a much better approach to get your data house in order as part of the move. Last week I discussed database normalization as ...

James McCaffrey explains how to normalize and encode neural network data from a developer's point of view.

This process of normalization involves converting data from its proprietary format so it can be used by any integrated solution, such as DCIM, BMS, ITSM, ERP and other applications that provide ...

Datorama’s Landing Zone solution puts data normalization and data connector technology under the hood for its agency and brand customers. The promise is to simplify the process of adding new data ...

When normalizing data structures, attributes congregate around the business keys that identify the grain at which those attributes derive their values. Attributes directly related to a person, ...

Summary In general, data normalization establishes a foundation for achieving semantic interoperability and creates an infrastructure that enables data sharing and aggregation.

Arguably, the two biggest challenges in the FAST ecosystem are managing the ad experience and delivering ROI for the brands that support the platform. Experts, from Fremantle's Laura Florence to Fuse ...