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 ...

Learn how to master Excel for data analysis and uncover actionable insights with this step-by-step guide. Perfect for beginners and pros ...

For design engineers, an artificial intelligence (AI) workflow encompasses four steps: data preparation, modeling, simulation and testing, and deployment. While all steps are important, many engineers ...

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 ...

Seagate is urging its channel to work with customers to establish the foundations for a successful artificial intelligence roll-out ...

Introduction to Big Data (DT102) provides the fundamentals needed to allow organizations to turn data into actionable information. Starting with an overview of big data, which covers key enterprise ...

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 ...

A new study published in Global Ecology and Biogeography presents a step-by-step guide to compile numerous fossil pollen datasets into a user-specific, standardized and clean compilation—ready for ...

Have you ever found yourself drowning in a sea of messy spreadsheets, spending hours manually cleaning and organizing data? For many Excel users, this is a frustratingly familiar scenario. But what if ...

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, ...