10.12-13.22-DigitalTech-Shah

Conference Video|Duration: 41:57
October 12, 2022
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    Physical to digital transformation has led to the rise of business “data operators”: individuals in organizations, from the ground level to the C-suite, who are using data as their primary “sensors” to run mission-critical operations. The day-to-day workflow of such a data biz operator requires accessing data from multiple sources, "stitching" them together, extracting current status as well as insights,  making decisions and communicating to the downstream task in a collaborative manner. While there are a number of tools for data analysts, data scientists and data engineers, the tool-set for data operators has been absent and subsequently leading to widespread reliance on spreadsheets.

    In this talk, we shall discuss how AI-native cloud-data platform can enable such data operators to "program" their biz ops seamlessly. We shall discuss how AI can enables stitching disparate data sources seamlessly with human-in-the-loop workflows. We shall also discuss the opportunities that can be realized by recent advances in causal inference and reinforcement learning for "what if" scenario analysis.
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  • Video details
    Physical to digital transformation has led to the rise of business “data operators”: individuals in organizations, from the ground level to the C-suite, who are using data as their primary “sensors” to run mission-critical operations. The day-to-day workflow of such a data biz operator requires accessing data from multiple sources, "stitching" them together, extracting current status as well as insights,  making decisions and communicating to the downstream task in a collaborative manner. While there are a number of tools for data analysts, data scientists and data engineers, the tool-set for data operators has been absent and subsequently leading to widespread reliance on spreadsheets.

    In this talk, we shall discuss how AI-native cloud-data platform can enable such data operators to "program" their biz ops seamlessly. We shall discuss how AI can enables stitching disparate data sources seamlessly with human-in-the-loop workflows. We shall also discuss the opportunities that can be realized by recent advances in causal inference and reinforcement learning for "what if" scenario analysis.
Locked Interactive transcript

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