🔧 Modern Data Processing Libraries: Beyond Pandas

As discussed in my previous article about data architectures emphasizing emerging trends, data processing is one of the key components in the modern data architecture. This article discusses various alternatives to Pandas library for better performance in your data architecture. 

Data processing and data analysis are crucial tasks in the field of data science and data engineering. As datasets grow larger and more complex, traditional tools like pandas can struggle with performance and scalability. This has led to the development of several alternative libraries, each designed to address specific challenges in data manipulation and analysis.