Real-Time Analytics: Answering the Five Ws of Unstructured File Data Management

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This week we announced a partnership with Fujitsu Europe to help enterprises meet the scale, performance, and cloud requirements for large-scale unstructured data environments. Our file data platform will help Fujitsu’s customers to effectively manage and leverage their file data, even when it’s distributed across complex hybrid IT environments.

Our partnership with Fujitsu (and our other technology platform partners) enables organizations to modernize their IT architectures, gain insight into their file data, and in turn, transform that data into strategic business value. For example:

  • Life Sciences – Scientists explore data captured from genomic sequencers to identify anomalies, then compute clusters transform the raw data into finished discoveries. Those discoveries are published to the research community, then the data is archived.
  • Media and Entertainment – Artists edit data captured from daily shoots to create initial scenes, then post-production transforms them into finished film. Distributors publish that film to online outlets, and the finished content is archived.
  • Manufacturing & IoT – Logs and images are generated from sensors (with high volume, velocity, and variety) and analyzed in real time for component failures. Later, business analysts review the data to explore opportunities for process improvements, and by data scientists to build better machine learning models. Those models are published into the manufacturing line to improve production efficiency, and finished logs and images are archived.

However, when we talk about that journey to “data-driven transformation,” we understand there might be some bumps along the road. Storing, accessing and managing petabytes of file data, especially when it is across several data centers and multiple clouds, is no easy feat. One of most common concerns we hear from new customers is the struggle to manage, let alone to derive value from, their unstructured file data.

Maybe you’ve struggled with “data blindness” and are unable to get an accurate view of what’s happening in your file system. Qumulo’s real-time analytics helps users to answer the “Five W’s” when it comes to file data management:

  • Who is accessing data?
  • What is causing slowdowns in data access?
  • When is this taking place?
  • Where are the issues?
  • Why are these issues occurring?

 

Qumulo’s file data platform is designed to provide visibility, no matter how many billions of files or how many directories there are. You can, for example, get immediate insight into throughput trending and hotspots. You can also set real-time capacity quotas, which enable administrators to make adjustments to usage thresholds long after the system is initially configured, providing them flexibility over time.

 

Potential performance issues, such as massive spikes in demand, and longer-term trends can be identified at-a-glance. Having this type of information allows for easier data management in distributed environments and provides the ability to absorb unpredictable, unstructured data growth and data demands from applications, both on and off the cloud. Information is accessible through a graphical user interface, and there is also a REST API that allows you to access the information programmatically.

Qumulo’s mission is to help organizations unleash the power of their data wherever it resides. This allows innovative companies to create new business models, treatments, products, and content by transforming data into value. Our community of technology platform partners, including Fujitsu, provide organizations with a choice of hardware and cloud infrastructure options and avoid vendor lock-in.

Ultimately this all means a smoother ride on the journey to data-driven transformation. Are you ready to hit the road?
Learn more about how you can achieve optimal performance for your workloads. Watch our 30-minute on-demand “Tech Talk Tuesday” webinar here, or contact us for a demo to get the conversation started.

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