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SAS Global Forum 2011 Data Integration Paper 1452011 Base SAS Methods for Building Dimensional Data Models Christopher W. Charterer, Clinical Data Management Systems, LLC ABSTRACT As the volume of

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To fill out base SAS methods, follow these steps:

1. Review the documentation: Before filling out the base SAS methods, it is essential to thoroughly review the documentation provided. This will help in understanding the purpose and usage of each method.
2. Understand the requirements: Determine the specific requirements or objectives for which the base SAS methods are being used. This could include data manipulation, statistical analysis, or generating reports. Understanding the requirements will guide the selection of appropriate methods.
3. Choose the relevant method: Base SAS provides a wide range of methods to perform various tasks. Identify the specific method(s) that align with the requirements and suit your needs.
4. Gather the necessary data: Before implementing the base SAS methods, ensure that you have the required data accessible. This can involve importing data from external sources or using pre-existing datasets within the SAS environment.
5. Implement the method(s): Once the relevant method(s) have been selected and the data is prepared, proceed with implementing the chosen method(s) one by one. Follow the syntax and guidelines provided in the documentation to correctly apply the method(s).
6. Test and debug: After implementing the base SAS methods, it is crucial to thoroughly test and debug the code. Ensure that the desired results are obtained and the code runs without any errors or warnings.
7. Analyze the output: Once the code executes successfully, carefully analyze the output generated by the base SAS methods. Verify whether it meets the desired objectives and evaluate the accuracy and reliability of the results.

Who needs base SAS methods for?

1. Data Analysts: Base SAS methods are valuable for data analysts who need to perform various data manipulation and analysis tasks. These methods provide efficient ways to sort, filter, summarize, and transform data.
2. Statisticians: Statisticians often require base SAS methods to perform statistical analysis and modeling. These methods enable them to conduct regression analysis, calculate descriptive statistics, perform hypothesis testing, and more.
3. Researchers: Researchers from various fields utilize base SAS methods for tasks such as data cleaning, merging datasets, and conducting exploratory data analysis. These methods help in making accurate and reliable conclusions based on the collected data.

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