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The large amount of information generated by any genomic study of a complex trait requires careful attention to quality control, efficient and secure storage, and compliance with data‐sharing requirements and privacy protections. These activities require a well‐designed and secure database system. Such systems have evolved over time from text files to relational databases, to large‐scale “data warehouses.” Such datasets also require large‐scale processing power with ample attached storage to facilitate linkage and association studies. High‐throughput sequencing in particular requires a large amount of storage and computational power for genome alignment (or assembly) and base calling. For multi‐site studies, these resources may need to be accessible from multiple locations, requiring levels of access and security depending on the role on the study and need to access other sites’ information. In addition to maintaining local resources for a study, a bioinformatics team also must be familiar with many different public sources of genomic data (e.g. UCSC and Ensembl browsers, ENCODE databases, sequence repositories, dbGaP) and be able to submit results to public repositories for sharing with the wider research community. These issues are discussed in more detail in Chapter 7.