HPE Ezmeral: Uncut

Learn how a data fabric can provide the foundation for business innovation

HPE World Watch Virtual Event! Mark your calendar: April 7th, 2021. HPE expert explains the importance of data motion, highlighting lessons learned from autonomous car technology.


The autonomous driving industry is paving the way for managing data motion at scale. A small fleet of autonomous cars may generate anywhere between 100 PB and 500 PB per day.[i] The ability to move massive data sets of varying types and locations across technology systems is a mandatory requirement of this business model. But data is only valuable when it is in the right place at the right time. 

In the driverless car example, large scale data sets and machine learning allow a computer to direct the steering wheel at the precise moment needed to turn a corner. To deliver this outcome, data scientists and engineers must focus on core data analysis, not data acquisition, data management, or the storage and motion of data. That same need for focus applies to data – no matter the scale.

The good news is a data fabric can handle all the data from field to core and can provide the foundation for scalable business innovation. Ted Dunning, Chief Technology Officer for HPE Ezmeral Data Fabric at Hewlett Packard Enterprise (HPE), will discuss this topic on April 7th during his webinar: World Watch—Data motion at scale: The untold story.

Highlights of this whiteboard walk-through include: 

  • Keeping focus on the data, not the logistics

How can organizations avoid becoming completely distracted by the mundane tasks of storing, managing, and moving data? Just as importantly, how can engineers doing data ingestion focus on ingestion while engineers doing machine learning focus on machine learning?

The key is a separation of concerns, and this separation applies to anybody working at scale, not just those building and analyzing cars.

  • The bigger the system, the bigger the potential issues

The explosion of data today makes everything more extreme for large-scale computing systems. The sheer volume of data is larger than any one computer can manage and that means coordination across multiple systems is needed. Because data is not centralized, organizations need to process data in many places. These logistical aspects of distributed data processing are much more complex than they appear, and they get dramatically more complex at scale.

  • A solution for solving data logistics

A data fabric can optimize away much of the distraction associated with data storage, management and motion—regardless of what you do with the data or where. Analytics, data science, and business teams can focus on creating real value from that data because the data fabric simplifies data management on a globally distributed scale.

Mark your calendar for this insightful session about solving data logistics and learn how data motion applies to workflows beyond autonomous car development.

You won’t want to miss this virtual event, World Watch—Data motion at scale: The untold story on April 7th.

[i] DEVELOPMENT OF A HIGHLY AUTONOMOUS DRIVING INFRASTRUCTURE. A technology blueprint overview. https://assets.ext.hpe.com/is/content/hpedam/a00091772enw


About the author:

Jenna Wernham 2.jpg

Jenna Wernham is an HPE Marketing Manager for the Americas and is focused on creating market insight content by leveraging primary customer research for key industries and workloads. For over 10 years at Hewlett Packard Enterprise, Jenna has focused on what digital transformation means to various customer audiences.




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