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#process-data-from-dirty-to-clean

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Process Data from Dirty to Clean - Module 4 challenge

Fill in the blank: A data scientist keeps code for data analysis pipelines in a _____, which enables them to track the evolution of the pipelines over time. changelog dashboard dataset version control system You are a data analyst working for ...

Apr 26, 20253 min read

DNDavid Nguyeneplus.dev

Process Data from Dirty to Clean - Module 1 challenge

Fill in the blank: If a test is statistically significant, the results are less likely to be due to _____ and more likely to be due to a real difference between the groups being compared. causation bias insufficient data random chance A compan...

Apr 26, 20253 min read

DNDavid Nguyeneplus.dev

Process Data from Dirty to Clean - Module 2 challenge

To identify ways to improve the shipping process, a data analyst merges a dataset of client order data with a dataset of shipping data. What should the data team do to ensure the compatibility of the two datasets? Spotcheck for null values Use a vi...

Apr 26, 20253 min read

DNDavid Nguyeneplus.dev

Process Data from Dirty to Clean - Module 3 challenge

A data professional analyzes medical data for a health insurance company. The dataset they are working with contains millions of rows of data. What tool would be most efficient for the analyst to use? SQL CSV Word processor Spreadsheet A junio...

Apr 26, 20252 min read

#process-data-from-dirty-to-clean

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#process-data-from-dirty-to-clean

Process Data from Dirty to Clean - Module 4 challenge

Process Data from Dirty to Clean - Module 1 challenge

Process Data from Dirty to Clean - Module 2 challenge

Process Data from Dirty to Clean - Module 3 challenge