Just because your data is unstructured doesn't mean it has to be incriminating Aperture data

Just because your data is unstructured doesn't mean it has to be incriminating Aperture data

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Data Council • Available on Youtube • Published 2 years ago
Just because your data is unstructured doesn't mean it has to be incriminating Aperture data
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Visual data (images/videos) are rich in valuable insights. Data science and ML techniques can help understand visual content and enable better customer experience across application domains, which in turn drives its exponential growth. A key factor for success in visual ML is getting the fundamental data infrastructure in place, which can be extremely challenging and time-consuming due to a lack of data management solutions designed with visual data or data science in mind.

In this talk I will start by briefly highlighting why visual data needs special treatment today and how this can be achieved. I'll also delve deeper into some of the architecture and design decisions that have worked well so far, as we've built such a database ourselves, and give you a quick preview of our product, ApertureDB, and where we're headed.

ABOUT THE SPEAKER
Vishakha Gupta-Cledat is co-founder and CEO of ApertureData. Previously, she spent more than seven years at Intel Labs, where she led the design and development of VDMS (the Visual Data Management System), which is at the heart of ApertureData's product, ApertureDB. Vishakha has a PhD in Computer Science from the Georgia Institute of Technology and an MS in Information Networking from Carnegie Mellon University. She has worked on scheduling in heterogeneous multi-core environments, graph-based storage and applications on non-volatile memory systems, and visual data management challenges for analytical use cases.

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