Amal leans back and looks at her notebook. Three pages filled. Plus four whiteboards covered in post-its from the requirements workshop. Somewhere in all of that are the business objects she needs for the new data model. "Diego," she asks, "how long did it used to take you to figure out what actually needed to be modeled after a workshop like this?" Diego smiles. "Back in the day? Sometimes a week."
AI systems require perfectly structured data but cannot create the necessary data models themselves. Why does even the most powerful AI fail to understand what a "customer" or "product" means in a specific company? And why is precisely this definition work the key to success for every AI implementation?
Artificial intelligence is currently revolutionizing virtually every business area. Yet amid all the enthusiasm for these technologies, a fundamental paradox is often overlooked: AI requires high-quality, structured data to function at all. At the same time, AI itself is unable to create the data structures it needs to work.
An EXASOL Webinar serie
We are back again after a long time, with a new webinar. The last one, we (Mathias and I) did together is almost four years ago. Time flies by! What's up this time?
The fictitious company FastChangeCoTM has developed a possibility not only to manufacture Smart Devices, but also to extend the Smart Devices as wearables in the form of bio-sensors to clothing and living beings. With each of these devices, a large amount of (sensitive) data is generated, or more precisely: by recording, processing and evaluating personal and environmental data.
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