Earlier this year Chris Johnson, the founding Director of the Scientific Imaging and Computing Institute, spoke with The Science Node about the collaborative nature of creating good data visualizations. In it, he explains that their process in making useful data visualizations involves more than a computer scientist laboring away alone at their desk. “Designing effective visualization tools and systems,” he said, “relies on input from domain experts and a continuous dialogue between them and computer scientists throughout the development process.”
By bringing in domain experts to collaborate with visualization researchers, organizations like The Scientific Computing and Imaging Institute is able to make visualizations that help us understand specific topics with very large and complex data sets. What if visualizations could be used to apply the same reasoning process to managing your own storage? For one, organizations would understand what is going on inside their figurative blackbox of storage. Further, it could help IT Managers collaborate with end users to define their workflows and implement a storage strategy that is tailor-fitted to their needs.
One of the examples Johnson gave in talking with The Science Node about collaborating to make visualizations was their work on a project called MizBee, which they created to explore conservation relationships in comparative genomics data. The domain experts in genomic research were looking at questions about evolution by comparing genomes of different species. But understanding the differences and similarities between genomes requires researchers to analyze large datasets. This is where working with visualization researchers becomes so valuable, in allowing biologists to interactively explore data in a visual way.
With storage environments getting into the peta-scale range of data, being able to interactively explore the usage patterns visually is a critical management tool. And like we heard from various storage experts before, the best storage strategy is one that matches your specific workflows. By using storage analytics and input from visualization researchers, SCI was able to do just that.
One of the less talked about challenges of data management is communicating storage resource availability to users and managers. How can you show someone what their storage usage patterns are, or why only a certain amount of capacity is available? By using Qumulo’s real-time analytics, Nick Rathke, Assistant Director of IT at SCI, brought researchers into the storage conversation by using visualizations.
“Everyone thinks their data is critical, but now when someone disputes the importance of a project that’s due to be archived, I can quickly pull up the dashboard to show that it hasn’t been touched in years. It adds clarity into an otherwise murky storage decision,” said Rathke on the value of storage analytics. Conversely, the real-time visibility enables Rathke to also show that sometimes, even though a file is old, it represents a data set that still gets used regularly.
In both instances, using visualizations not only allowed Rathke to reason about his team’s data, but it also made those insights available to a wider audience. And in environments like SCI that run high performant workloads, having organization-wide visibility into the storage could help maintain user best practices for data governance.
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