Workflows in life sciences and bioinformatics are characterized by massive volumes of machine-generated file data that is pipelined into downstream processes for analysis. With today’s sequencer technology, most experts agree that about 100 GB of data is generated for each human genome that is sequenced.
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With the Earth’s population predicted to eclipse 8 billion people by 2025, some researchers believe that Life Sciences and Genomics in particular will soon become the single largest producer of new data across all media types — outpacing today’s leaders like YouTube, Twitter, and astronomical research.
Legacy file storage fails to provide researchers with acceptable performance and cost effectiveness at petabyte scale, especially with the wide mix of file sizes that characterizes modern research workflows.
But it’s not all bad news.
Balancing researcher, IT, and executive team concerns, watch this video case study about the Department of Embryology at the Carnegie Institution for Science, and see why they turned to Qumulo’s modern scale-out storage to deliver the performance, scalability, and simplicity needed to keep pace with evolving research data requirements.