Data scientists begin by identifying the type of data required—structured, semi-structured, or unstructured—and determining whether the data will be sourced internally, externally, or through a combination of both. Common data collection methods include surveys, interviews, web scraping, application logs, sensors, APIs, transactional systems, and publicly available datasets. Each method has its strengths and limitations, so selecting the right approach depends on factors such as data volume, frequency, cost, accuracy,data collection strategies in data science and ethical considerations.