Life Sciences Storage FAQ

Why is there such a drastic explosion in life sciences data?
 The cost of genomic sequencing has dropped faster than Moore’s Law. Coupled with the growth of next-generation sequencers, most enterprise IT departments are ill-equipped to keep the pace with the rapid development of scientific instrumentation and data generation.

What does this data explosion mean for organizations focused on life sciences research?
 Solutions that address input, compute, storage, and derived data needs are lagging behind the rapid pace of scientific innovation that is generating this increased amount of data. Organizations must identify the most cost-effective solutions that allow them to simultaneously address their ever-increasing research needs, while considering the tradeoffs between various solutions.

 Why is NAS a better solution for many organizations focused on life sciences research?
 First, the data explosion in life sciences means that there must be a tradeoff between capacity and performance. Most organizations will choose the former. Additionally, organizations prefer solutions that require fewer resources to operate and manage. This choice of simplicity over capabilities means that NAS scale-out solutions are typically preferred over larger SAN solutions.

 How can NAS solutions help organizations focused on life sciences research?
 Research has become so multidisciplinary that life science data is being used by a variety of researchers and scientists, from enterprises to individual researchers at universities. Data analysis is often discipline-specific, requiring differing tools and highly variable workloads. NAS solutions provide cost-effective, scalable, reliable, and high-capacity solutions for organizations generating and using large amounts of data.

 What are the main storage requirements for life sciences research? What are some of the benefits of a scale-out approach to storage?
For enterprises conducting life sciences research, a scale out approach can mean the difference between large, costly technology overhauls versus smaller, cost-effective, and planned updates. Scale-out approaches incrementally add or replace storage for a fraction of the cost of a complete overhaul. Using this approach, there is no need for a large IT update expense in any single fiscal year. Next, any issue with a component does not disrupt access to data. All data is simply migrated to another node while issues are addressed. Finally, it is much simpler to create a tiered-data solution with scale-out storage.
Have more questions to be added to our Life Sciences FAQ? Let us know and we will be happy to answer them!

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