PharmaGlobal, a multinational pharmaceutical company, is developing a novel drug targeting a rare genetic disorder. Their research and development efforts are distributed across four international sites: Site Alpha (USA), Site Beta (Germany), Site Gamma (Japan), and Site Delta (India). Each site specializes in different aspects of the drug development process. Site Alpha focuses on clinical trial data collection, Site Beta handles chemical composition analysis, Site Gamma manages patient demographics and genetic information, and Site Delta is responsible for regulatory compliance documentation. The data generated by each site is stored in separate, non-integrated systems, utilizing different data formats and quality control procedures. Initial analysis reveals significant discrepancies in how patient identifiers are recorded (e.g., date formats, naming conventions), inconsistencies in chemical compound naming across sites, and varying levels of detail in regulatory submissions. The regulatory submission deadline is rapidly approaching, and the company needs to consolidate and analyze all the data to demonstrate the drug\'s safety and efficacy. Manufacturing plans are contingent on successful regulatory approval. Given the disparate systems and data inconsistencies, which dimension of data quality should PharmaGlobal prioritize addressing FIRST to ensure a successful regulatory submission and subsequent manufacturing readiness?