Data analysis serves a critical role in examination processing, from estimating the statistical item characteristics used in test assembly and standard setting through score scale development and maintenance, and score reporting. This chapter provides an overview of the primary analysis steps and types of data used in processing credentialing examinations, together with common scenarios, challenges, and solutions typically encountered in practice. It covers four relatively broad data analysis steps needed to process most types of credentialing examination programs: data preparation, item analysis, scale analysis, and examinee scoring and reporting. Credentialing examination programs that may be transitioning toward increased use of performance-based tasks and technology-enhanced test items may further need to plan for changes in the nature of the item subcomponents and examinee "transactions". Those will almost certainly become more elaborate, possibly requiring innovative scoring and analysis procedures. Data quality control (QC) needs to be a top priority for any credentialing examination program.