Implementing AI in healthcare isn’t just about choosing the right tools—it’s about making them work in the real world.

Environmental data should be treated with the same rigor as financial data. Yet too often, it’s still used to support ...

The CLEAN framework is a structured, five-step methodology for data cleaning: Conceptualize, Locate, Evaluate, Augment, and Note, aimed at addressing data issues systematically and transparently.

Before you resell, recycle, or donate an old laptop or desktop, learn how to wipe a computer clean and protect your personal data.

AI-powered data cleaning tools use machine learning algorithms to automate data cleaning tasks such as data profiling, data matching, and data standardization.

It's time for spring cleaning, including your enterprise data stores, says data expert Joey D'Antoni, who offers front-line data-hygiene advice straight from the IT trenches.

Philadelphia's annual street-sweeping program resumed Tuesday to clean up blocks in 14 neighborhoods known for having higher-than-average litter problems, city officials said.

The mechanical cleaning program returns this week as part of the city’s continued effort to crack down on litter in Philadelphia neighborhoods.

Learning to program in C on an online platform can provide structured learning and a certification to show along with your resume.

Her project, “From Dirty Data to Fair Prediction: Data Preparation Framework for End-to-End Equitable Machine Learning,” targets the data-preparation pipeline as a strategic opportunity for ...

Data cleaning is an essential step in data analysis. Inaccurate or inconsistent data can lead to incorrect conclusions and poor decision-making. Microsoft Excel, a powerful tool for data ...

Learn about the most important tools for data cleaning in statistical programming languages and tools, such as R, Python, SQL, SAS, and SPSS.