exam 2 study guide.docx

exam 2 study guide.docx - ETL Extract transform and load...

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ETL Extract, transform, and load Reasons why: Look for mistakes, prepare for analysis, combine the sources What does it mean for data to be “dirty?” Inaccurate data, has errors How does data get dirty? - What are the consequences? Some well-known examples? Stop trusting source and data that you have Mistakes lead to bad decisions with negative consequences Government debt case and neglected to copy over 5 major countries Lehman brothers purchase, buying toxic assets since the cells were hidden - Explain the impact of bad data on future decision-making processes. Answer How do you clean it? - How should you deal with outliers? Go back to source first to check and see if numbers are correct Take a data out, and average the rest and substitute Last resort is to remove - How do you deal with ambiguous data (i.e., when you don’t know what the label means)? Look at metadata or data dictionary to see if data and items are the same Backup plan: go back to the source What is a KPI?
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