Transforming data | Coursera

In this reading, you will explore how data is transformed and the differences between wide and long data. Data transformation is the process of changing the data’s format, structure, or values. As a data analyst, there is a good chance you will need to transform data at some point to make it easier for you to analyze it. Data transformation usually involves: Adding, copying, or replicating data Deleting fields or records Standardizing the names of variables Renaming, moving, or combining columns in a database Joining one set of data with another Saving a file in a different format. For example, saving a spreadsheet as a comma separated values (.csv) file. Goals for data transformation might be: Data organization: better organized data is easier to use Data compatibility: different applications or systems can then use the same data Data migration: data with matching formats can be moved from one system to another Data merging: data with the same organization can be merged together Data

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