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Paper A022009 Using PRO LAP to Build Cubes with Nonaddictive Measures Ben Cochran, The Bedford Group, Raleigh, NC ABSTRACT Most of the time, LAP cubes are built from data that has additive measures,
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01
First, gather the necessary data for analysis. This could include sales figures, customer information, or any other relevant data that you want to analyze using PROC OLAP.
02
Next, open the SAS program and load the necessary libraries and datasets. Make sure you have the PROC OLAP library available.
03
Use the PROC OLAP statement to start the analysis. Include the necessary options and parameters to specify the data and variables to be used in the analysis.
04
Specify the dimensions and measures that you want to include in the analysis. Dimensions are the categorical variables that you want to use to group or categorize the data, while measures are the numeric variables that you want to analyze.
05
Apply any necessary filters or conditions to narrow down the data being analyzed. This can be done using the WHERE statement or other filtering options within PROC OLAP.
06
Specify any additional options or parameters to customize the analysis. This could include options for calculating summary statistics, creating cross-tabulations, or defining custom measures.
07
Run the PROC OLAP code and review the results. Make sure the output is as expected and meets the requirements of the analysis.
08
If needed, save the results to a SAS dataset or export them to another format for further analysis or reporting.
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Finally, document the analysis steps and results for future reference or to share with others who may need to understand or replicate the analysis.

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Data analysts who want to perform advanced analysis on large datasets.
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Using proc olap to allows users to create and manipulate OLAP cubes in SAS software.
Individuals or organizations who need to analyze data in a multidimensional way may use proc olap to.
To use proc olap to, users need to write SAS code to create, query, and manipulate OLAP cubes.
The purpose of using proc olap to is to perform complex analysis on multidimensional data cubes.
Users can report on various dimensions and measures within the OLAP cubes, including sales data, customer information, and product performance.
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