How Operationalized Data Solves Customer Engagement Problems & Achieves Business Goals
- Nov 23, 2020 11:51 pm GMT
This item is part of the Special Issue - 2020-12 - Data Analytics & Intelligence, click here for more
When you think about data, you might imagine a dizzying array of ones and zeroes, or spreadsheets filled with minute details. But as a data scientist and machine learning evangelist, I see data as a rich collection of tools and materials for solving real-world problems.
Like the bricks, boards, screws and sheets of drywall you’d assemble to build a house, data can (and should) be architectured purposefully to create something of value that’s safe, reliable, familiar and useful for years to come.
I call this process ‘operationalizing’ data, and anyone can do it if they want to make better, data-backed business decisions that solve customer engagement problems. That’s because operationalized data, especially when it’s infused with A.I., is fully functional, responsive, predictive and useful for fixing problems as they arise, even if you’re not a data guru, yourself.
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