{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T09:49:03Z","timestamp":1770457743187,"version":"3.49.0"},"reference-count":19,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T00:00:00Z","timestamp":1639699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"crossref","award":["UL1 TR002535"],"award-info":[{"award-number":["UL1 TR002535"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100011866","name":"Colorado Clinical and Translational Sciences Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100011866","id-type":"DOI","asserted-by":"publisher"}]},{"name":"UCHealth, Childrens Hospital Colorado"},{"DOI":"10.13039\/100010174","name":"University of Colorado","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010174","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Clinical research data warehouses (RDWs) linked to genomic pipelines and open data archives are being created to support innovative, complex data-driven discoveries. The computing and storage needs of these research environments may quickly exceed the capacity of on-premises systems. New RDWs are migrating to cloud platforms for the scalability and flexibility needed to meet these challenges. We describe our experience in migrating a multi-institutional RDW to a public cloud.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>This study is descriptive. Primary materials included internal and public presentations before and after the transition, analysis documents, and actual billing records. Findings were aggregated into topical categories.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Eight categories of migration issues were identified. Unanticipated challenges included legacy system limitations; network, computing, and storage architectures that realize performance and cost benefits in the face of hyper-innovation, complex security reviews and approvals, and limited cloud consulting expertise.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Cloud architectures enable previously unavailable capabilities, but numerous pitfalls can impede realizing the full benefits of a cloud environment. Rapid changes in cloud capabilities can quickly obsolete existing architectures and associated institutional policies. Touchpoints with on-premise networks and systems can add unforeseen complexity. Governance, resource management, and cost oversight are critical to allow rapid innovation while minimizing wasted resources and unnecessary costs.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Migrating our RDW to the cloud has enabled capabilities and innovations that would not have been possible with an on-premises environment. Notwithstanding the challenges of managing cloud resources, the resulting RDW capabilities have been highly positive to our institution, research community, and partners.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocab278","type":"journal-article","created":{"date-parts":[[2021,12,3]],"date-time":"2021-12-03T20:11:51Z","timestamp":1638562311000},"page":"592-600","source":"Crossref","is-referenced-by-count":27,"title":["Migrating a research data warehouse to a public cloud: challenges and opportunities"],"prefix":"10.1093","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4786-6875","authenticated-orcid":false,"given":"Michael G","family":"Kahn","sequence":"first","affiliation":[{"name":"Section of Informatics and Data Science, Department of Pediatrics, University of Colorado School of Medicine, Aurora, CO, USA"},{"name":"Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, 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