Academic research labs perform data-intensive scientific research that create ever larger data sets. Resulting data management challenges are varied as technological advancements have outpaced traditional storage solutions. Universities need flexible storage solutions that can integrate with existing infrastructure and affordably deliver the high performance, access and scale required for scientific innovation.
Artificial intelligence (AI), machine learning (ML) and deep learning (DL) are disruptive technologies that are transforming how business processes are run in the digital age. Using AI to make better, more informed decisions requires collecting and accessing massive, complex data sets for rapid iteration during training, validation and simulation workflows. To eliminate bottlenecks in model iteration and delays in value realization, organizations need flexible, scalable storage platforms.
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Government agencies and labs need to store and rapidly access huge data volumes for complex modeling, simulations and analytics. However, they are largely limited in delivering on their missions due to legacy storage infrastructures. Government agencies need flexible storage solutions to support these data-intensive processes that can integrate with existing infrastructures and affordably deliver the high performance, access and scale required for mission-critical environments.
In financial services, the need for speed drives competition but imposes demanding requirements on storage infrastructure. Getting actionable data as fast as possible from massive data volumes requires even faster data transfer, access and storage. Traditional storage solutions have been outpaced. Financial institutions, brokerage firms, hedge funds, and prop trading require flexible storage solutions that integrate with existing infrastructure and cost-effectively deliver the high performance, access and scale required for faster workflows.
Recent advances in video resolution, sensor technologies and software for processing geospatial data equate to vast opportunities in the geospatial space. However, with these technology advances comes enormous storage and archive challenges as geospatial analysts struggle to keep pace with the massive influx of satellite imagery and data. Geospatial workflows require flexible storage solutions integrate with existing infrastructure and affordably deliver the high performance, access and scale.
Life sciences researchers and scientists need to store and rapidly access huge data volumes in high-performance applications like bioinformatics, genomics and drug discovery. However, they are largely limited in accelerating time to results due to legacy storage infrastructures. The research community needs flexible storage solutions to support data-intensive processes that can integrate with existing infrastructures and affordably deliver the high performance, access and scale required for scientific discoveries and breakthroughs.
National labs push the boundaries of science, engineering and technology with data-intensive research that creates massive volumes of data. Researchers need flexible storage solutions that can integrate with existing infrastructure and affordably deliver the high performance, access and scale required for groundbreaking discovery.
Next generation security and surveillance systems need to support higher resolutions, growing camera and sensor counts and real-time analytics. Legacy storage infrastructures are not able to keep up. Choosing the right high-performance storage platform is vital for video surveillance organizations to ensure the reliability, availability and serviceability of real-time video surveillance and archived data.
