ml-specialty video for a financial analytics firm receives continuous streams of transaction data, each record populated with hundreds of columns, the firm
A financial analytics firm receives continuous streams of transaction data, each record populated with hundreds of columns, the firm faces a challenge. A significant portion of this data is irrelevant to their machine learning model, which aims to predict transaction fraud. Additionally, certain relevant columns require minor transformations or concatenation. What is the most straightforward and storage-efficient method to preprocess this data upon its arrival?