From the course: Amazon Web Services: Data Analytics

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Data hygiene and ETL

Data hygiene and ETL - Amazon Web Services (AWS) Tutorial

From the course: Amazon Web Services: Data Analytics

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Data hygiene and ETL

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- [Instructor] Another concept we need to consider before we get started working with AWS Analytics, is data hygiene. As I mentioned in a previous movie, in our examples, our data will be clean, pristine, and easy to understand. And I'll be honest, and tell you this does not reflect the real world. It does allow us to focus on what the services do, which is important for this course. But again, I always like to bring my real world experience into what I share with my students. So what I find with my customers, is that very very frequently they need to invest significant resources in data hygiene, at the beginning of any new analytics project that I work with them on. So the concepts around this have the letter E in them. So let's just talk about those. What is ETL? Extract, transform, and load. The idea here, is that to build an analytic solution, you're going to need to design a process that's going to retrieve data out of a number of source systems, clean or transform the data…

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