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Data Management Trends You Need to Know

Intel Capital’s Assaf Araki and I both focus on data, analytics, and machine learning, thus we regularly hear pitches from startups building new data management solutions. Data management is a broad area that includes solutions for different workloads, data types, and use cases.  Our post lists reasons and key trends underlying our bullishness in this space, along with considerations data teams and platform architects should keep in mind as they evaluate data management solutions in the months to come.

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Data Exchange podcast

  • Delivering Continuous Intelligence at Scale: Simon Crosby – CTO of Swim and one of the founders of Xen Source –  describes next generation data infrastructure that enables applications to stay in sync with and learn from the real-world.
  • NLP and Language Models in Healthcare and the Life Sciences: Applications of NLP in Healthcare, Pharma, and the Life Sciences pose a number of challenges and considerations that differ substantially from other business verticals. Dia Trambitas-Miron and David Talby explain how lessons from these domains translate to other sectors.
  • The Graph Intelligence Stack: Graph Neural Networks is a hot topic among researchers, and it’s just a matter of time before graphs become a standard method to analyze data for operational insights. Graphistry CEO Leo Meyerovich and I discuss how you can begin incorporating tools for graph intelligence.
[Industry Interest in select Machine Learning frameworks.]

Data & Machine Learning Tools and Infrastructure

[Interest within Research Community – select deep learning frameworks.]

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