Use the MD Retirement Systems Report - Load page to extract and load employee retirement data into the Maryland retirement staging table for state reporting. The data is used to generate Maryland State Retirement and Pension System reports and electronic files.
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On the MD Retirement Systems Report page, select Load.
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Refer to the Field descriptions and enter or select the required load criteria.
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Select Load, and then Yes.
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If data for the selected criteria is loaded, select Yes to delete and reload the data.
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Save the Load Summary report file and select OK.
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If errors are encountered, save the Load Error log and select OK.
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Navigate to the file location.
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Inspect the files. Refer to Maintain data and update the data as necessary.
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Repeat these steps until no errors are encountered and all required data is loaded.
Field descriptions
The following table describes the fields on the MD Retirement Systems Report - Load page.
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Field |
Description |
|---|---|
|
Start Date |
The beginning of the payroll check date range for which retirement data will be extracted and loaded into the Maryland State Retirement Systems reporting file. |
|
End Date |
The ending of the payroll check date range for which retirement data will be extracted and loaded into the Maryland State Retirement Systems reporting file. |
|
Payroll End Date |
The pay period ending date that will be associated with the extracted retirement data for reporting purposes. |
|
Load Hours |
Indicates whether summer hours should be included in the retirement data extraction. When this option is selected, the system loads hours worked during summer periods for applicable employees. |
|
Talbot Summer Class Criteria |
Specify employee classification codes for which hours should be set to zero during the load process. This is typically used to exclude hours for specific employee classes that should not have hours reported during certain periods. |
|
Primary Pay Group |
Use this option to filter the data extraction by specific pay groups. If left blank, all pay groups are included in the retirement data load. |