Transforming an underlying Data Table from Short/Wide to Tall/Skinny format is known as

Transforming an underlying Data Table from Short/Wide to Tall/Skinny format is known as
A . Calculation
B . Unpivot
C . Renaming Columns
D . Pivot
E . Normalization

View Answer

Answer: B

Explanation:

Unpivoting is a transformation method that changes the data table from a short/wide format to a tall/skinny format. This means that multiple columns are combined into one or a few columns, and the number of rows increases accordingly. Unpivoting can be useful when you want to analyze the distribution of data across different categories or values, or when you want to apply other transformations or calculations on the data.

Unpivoting can be done either when loading data or after the data has been loaded into Spotfire. To unpivot data, you need to select which columns to keep as they are (category columns) and which columns to merge into one or more value columns (value columns). You can also specify the names of the new columns and the data types of the value columns. References: Unpivoting Data, Transforming Data, Spotfire Tips & Tricks: Normalize/Standardize your data with Spotfire