Intelligent Data Exploration

Intelligent Data Exploration

By VirtualiticsTechnology
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Intelligent Data Exploration episodes

  • Optimizing maintenance, logistics, and supply management with Virtualitics
    Just how “predictive” is your predictive maintenance? Are you only looking at the time to failure, or are you considering the supply chain, time to repair, and technician availability, too? Our platform shows how each element impacts your overall mission readiness—and how we can help your teams optimize their efforts. Check out our latest blog by Jerami Reyna, Virtualitics Solution Leader and retiring Air Force veteran with 20 years of aircraft maintenance experience on A-10 and B-52 weapons systems.
    6 min
  • Nine Steps to Building a Scalable AI Strategy
    AI is on the brink of becoming mainstream, but many organizations aren’t even attempting to use AI yet. Where does your team fall on that spectrum?No matter where you are on the AI maturity curve—just getting started or preparing to dive deeper—our experience has shown that there are nine steps to creating a successful AI strategy.
    8 min
  • How to overcome your biases and get better results from data exploration

    When we think of AI we tend to think of predictive models and supervised learning. But AI can be applied to exploration and understanding or data right from the start, leading to better business value. Co-head of AI, Aakash Indurkhya sits down with author and data scientist, Tobias Zwingmann to talk about how hypothesis-driven exploration isn’t getting the job done and is leaving valuable insight on the table, and setting you up for underwhelming AI. Join us as we discuss how using AI to explore data (Intelligent Exploration):

    • Discovers high-impact insight that you may have overlooked
    • Clarifies where you should direct your AI resources by uncovering good use cases and assessing feasibility
    • Helps remove the bias from your exploration

    Author Tobias Zwingmann helps BI professionals, business analysts and data analysts understand high-impact areas of artificial intelligence. You'll learn how to leverage popular AI-as-a- service and AutoML platforms to ship enterprise-grade proofs of concept without the help of software engineers or data scientists.

    Learn more about Virtualitics at virtualitics.com and see the slides with transcript here - https://blog.virtualitics.com/how-to-overcome-your-biases-and-get-better-results-from-data-explorati0



    57 min
  • The Keystones of Responsible AI: Explainability and Visualizations

    The future is no-code or low-code, but as more and more companies implement AI solutions and enable non-technical users,  how do you maintain accuracy and responsible use?

    The answer: explainable AI paired with multi-dimensional visualizations. These combined provide a more complete picture of the story playing out in a predictive system and are a must for ensuring responsible AI applications. 

    Join Caitlin Bigsby, Head of Product Marketing, as she sits down with Virtualitics’ Co-Heads of AI, Sarthak Sahu, and Aakash Indurkhya to discuss ways to incorporate visualizations into the ML lifecycle and key considerations.

    42 min

About Intelligent Data Exploration

From the publisher's feed

Data exploration is the foundation of all your data-driven initiatives. And as those initiatives expand to include AI, data professionals need to get smarter about how they explore their data. If you…