I work at a large financial organization.
I have been wondering what types of problems (=use cases) can be solved/optimized using the Edge AI technology in industries such as Banking and Finance, Power and Land and Agriculture?
I appreciate your thoughts and suggestions.
AI has already been used for decades in banking, finance and agriculture.
Credit and loan analysis use a lot of logistic regression to know who to loan money to. Finance uses AI for regression analysis of forecasts and optimum stock portfolios, agriculture to predict production and supplies needs based on the amount of rain forecasted.
What we have is the evolution of tools, methods and techniques. We no longer need cubes. Although Hadoop is meant for safe storage at low cost and not for AI purposes, tools have evolved and new tools arose providing the speed required for AI analysis.
We have evolved in terms of data governance with the use of DMBoK (Data Management Body of Knowledge), visual planning frameworks like the Machine Learning Canvas, Self Service BI approaches stimulating collaboration amongst users. We now have tools, practices, frameworks and enough manpower that makes the job more challenging.
We have been using AI in those sectors for quite a while, but now we have the momentum to reach a different level of data thinking organizations.
Aside from dashboards, there are some use cases that require a fair amount of detailed data, with customizable sort and display fields which can vary by account.
This is in the insurance, healthcare, benefits space in particular.
While advanced visualization features help on the dashboard side of the equation, I would like to get the opinion on the best tools for this detailed, ...
Senior Manager at a tech services company with 1-10 employees
25 January 22
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