QUESTION: 21

Identify the function of the Pivot transformation

Pivots row values into columns of data
Pivots column values into rows of data
Pivots row values to eliminate duplicates
Pivots column values to summarize correlated data

Answer(s): A

Explanation:

A pivot transformation is one way to transform data from a tall/skinny format to a short/wide format. The data is distributed into columns, usually aggregating the values. This means that multiple values from the original data end up in the same place in the new data table. A pivot transformation requires selecting row identifiers, column titles, values and aggregation methods, and optionally transfer columns and aggregation methods12. The function of the pivot transformation is to pivot row values into columns of data, based on the chosen parameters34.

Reference:

Pivoting Data - TIBCO Software
Details on Pivot Data - TIBCO Software
Transforming Data - TIBCO Software
Transforming Data - TIBCO Software

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QUESTION: 22

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

Calculation
Unpivot
Renaming Columns
Pivot
Normalization

Answer(s): 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.

Reference:

Unpivoting Data, Transforming Data, Spotfire Tips & Tricks:
Normalize/Standardize your data with Spotfire

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QUESTION: 23

Which custom expression function is used by when you auto-bin a numeric column?

BinByEvenDistributionQ
AutoBinNumeric()
AutoBinByLimitsO
BinBySpecifieLimits()
BinByStdDev()

Answer(s): B

Explanation:

AutoBinNumeric() is a custom expression function that is used when you auto-bin a numeric column. This function creates a binned column where the value range is divided into intervals based on the number of unique values and the distribution of the data. The function takes one argument, which is the column to bin, and returns a string column with the bin labels. The function is equivalent to right- clicking on a column selector and selecting Auto-bin Column, which creates a temporary, automatic binning on an axis. The function can be used in custom expressions to create permanent binned columns or to apply binning to other visualizations.

Reference:

AutoBinNumeric, How to Use Binning

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QUESTION: 24

Which of the following binning functions can be used on a numeric type column?

BinByTimeSpan()
BinByOateTime()
BinByEvenDistribution()
BinByNumbers()
BinBySubstring()

Answer(s): C

Explanation:

BinByEvenDistribution() is a binning function that creates a binned column where each bin has the same number of unique values as the others. The last bin may have more unique values than the others. The first argument is the column to bin and the second argument is the number of bins. This function can be used on a numeric type column to group the values into equal frequency bins. The other binning functions are either not valid (BinByTimeSpan(), BinByNumbers()) or not applicable to a numeric type column (BinByDateTime(), BinBySubstring()).

Reference:

Binning Functions, How to Use Binning

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QUESTION: 21

Explanation:

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QUESTION: 22

Explanation:

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QUESTION: 23

Explanation:

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QUESTION: 24

Explanation:

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