Data preparation can be complicated. Get an overview of common data preparation tasks like transforming data, splitting datasets and merging multiple data sources. Image: Artem/Adobe Stock Data ...

We live in a data-rich world where information is ours for the taking. But throwing just any data at your algorithm is a bad idea. With AI, small inconsistencies quickly become big ones. And those ...

Making the process of data wrangling easier and faster for a wider set of sources and deployment environments is critical to enterprise adoption,” said Stewart Bond, research director, IDC. Trifacta ...

Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...

Data preparation is an important step in any data analysis. This article offers suggestions for making that process easier and more effective. TechRepublic Get the web's best business technology news, ...