From the course: Predictive Analytics Essential Training: Data Mining

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Hints on effective data integration

Hints on effective data integration

From the course: Predictive Analytics Essential Training: Data Mining

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Hints on effective data integration

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- [Keith] I was working on a cell phone loyalty project some years ago, and I wasn't able to get access to any variables that recorded dropped calls. This might sound surprising at first. While I was working with the customer relations team, and as they explained it to me, Keith, customers don't have dropped calls, towers do. So I had to involve the engineers to get at that data. Now as it turns out, it wasn't a top variable, but it was strong enough to get incorporated into the final predictive model. It takes disparate data sources to make good models. So our next element is data integration. Something that every project needs is extensive data integration. Now I know we might think that through data warehouses and tools that engage in automated data blending, that this problem is somewhat resolved. But in my experience, it really isn't. In order to have a successful project, you want as many different sources of data…

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