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Your Payroll Processing Data Template

UKG Pro

Payroll Processing Attributes (20) Payroll Processing Activities (15) Extraction Guides (2)

Your Payroll Processing Data Template

This template provides the structural foundation for mapping your payroll cycles within UKG Pro to gain actionable insights. It details the necessary attributes for deep analysis, the specific process steps you should monitor, and instructions for gathering this information from your system environment. By aligning your data with this template, you can effectively pinpoint inefficiencies and ensure payroll compliance.

Standardized data attributes for payroll analysis
Essential process milestones to track in UKG Pro
Technical extraction guidance for system integration

New to event logs? Learn how to create a process mining event log.

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Payroll Processing Attributes

This table identifies the recommended data fields and contextual metadata required to build a comprehensive event log for your payroll process analysis.

5 Required 12 Recommended 3 Optional

	Name	Description
	Activity ActivityName	The specific event or step performed in the payroll process.
Description This attribute captures the name of the step occurring within the payroll workflow, such as Time Sheet Submitted, Gross Pay Calculated, or Payment Executed. It defines the flow of the process map. These values are typically extracted from audit logs, system status change tables, or timestamped transactional updates within the UKG Pro environment. Consistent naming conventions are applied during data transformation to ensure readability in the process graph. Why it matters This is the mandatory Activity attribute that defines the nodes in the process map. Where to get System Audit Logs, Workflow History, or Transaction Timestamp columns Examples Time Sheet SubmittedGross Pay CalculatedPayment Executed
	Last Update Date LastUpdateDate	The timestamp of the most recent modification to the data row.
Description This attribute indicates when the record was last changed in the database. While similar to the event timestamp, it is specifically used for incremental data loading and data integrity checks. It ensures that the process mining model reflects the most current state of the payroll record, capturing any late adjustments or retroactive corrections made by payroll specialists. Why it matters Mandatory attribute for incremental data refreshing. Where to get System metadata columns like LastModifiedDate Examples 2023-10-05T17:00:00Z2023-10-06T09:00:00Z
	Payroll Record PayrollRecordId	Unique identifier representing a specific employee within a specific pay period.
Description The Payroll Record acts as the central case identifier for the process mining analysis. It is conceptually constructed by combining the Employee ID and the Pay Period End Date (or Pay Group instance). This ensures that every payroll cycle for an individual employee is treated as a distinct case, allowing for the analysis of recurring processes over time. In UKG Pro, this is typically a composite key derived from the Payroll Header table or similar transactional records. Grouping by this ID allows analysts to reconstruct the end-to-end journey from time sheet submission to final payment and tax filing. Why it matters This is the mandatory Case ID that groups all payroll activities together to form a process instance. Where to get Derived from UKG Pro Payroll Header or Employee Pay History tables Examples EMP001-20231015EMP492-20231031EMP883-20231115
	Source System SourceSystem	The system of record for the data.
Description This attribute identifies the origin of the data record. In this specific context, the value is statically set to UKG Pro (or the specific instance name if multiple exist). This is crucial for multi-system process mining where payroll data might be blended with general ledger data from an ERP. It allows analysts to filter views to show only steps originating strictly within the payroll platform versus those that might be integrated from external time-keeping systems. Why it matters Mandatory attribute for data lineage and multi-system analysis. Where to get Static value or System Configuration table Examples UKG ProUltiPro LegacyTime Management System
	Timestamp EventTimestamp	The date and time when the activity occurred.
Description This attribute records the exact moment an activity took place. It is essential for sequencing events correctly and calculating durations between steps. High precision timestamps are preferred to distinguish between automated steps that happen in rapid succession. In the context of Payroll, this drives the dashboard analysis for Cycle Time Distribution and SLA Compliance. Without accurate timestamps, it is impossible to measure the velocity of Gross to Net calculations or the delay in Time Sheet Approvals. Why it matters This is the mandatory StartTime attribute required to sequence events. Where to get Date/Time columns associated with transaction status changes Examples 2023-10-01T09:15:00Z2023-10-01T14:30:45Z2023-10-03T08:00:00Z
	Cost Center CostCenter	The cost center code for financial allocation.
Description The Cost Center attribute defines where the payroll expense is allocated in the general ledger. While similar to Department, it often provides a more granular financial view. This attribute is used in the Time Tracking Approval Performance dashboard to identify if specific cost centers have slower approval hierarchies. It also helps in validating that payroll expenses are flowing to the correct financial buckets during the Gross to Net calculation phase. Why it matters Supports financial analysis and identifies bottlenecks by budget unit. Where to get Employee Job or Allocation tables Examples CC-5001CC-9002Overhead-Corp
	Cycle Time (Days) CycleTimeDays	Total duration from initialization to payment execution.
Description This duration attribute measures the end-to-end time of the process for each record. It underpins the Payroll Cycle Time Distribution dashboard. Analyzing the variance in Cycle Time Days across different Pay Groups or Departments reveals inefficiencies and helps quantify the impact of manual corrections on the overall process speed. Why it matters Core metric for process efficiency. Where to get Calculated: Payment Timestamp - Initialization Timestamp Examples 3.55.01.2
	Department DepartmentCode	The department code associated with the employee.
Description This attribute links the payroll record to a specific organizational unit. It is essential for the Audit Exception and Correction Trends dashboard, allowing the organization to see which departments consistently generate errors or require manual intervention. By segmenting data by Department, analysts can identify if specific managers need training on time sheet approval processes or if certain business units have complex pay rules causing calculation delays. Why it matters Critical for organizational segmentation and root cause analysis. Where to get Employee Master or Job History tables Examples DEPT-100FINANCE-01OPS-WEST
	Gross Pay Amount GrossPayAmount	The total pay calculated before deductions and taxes.
Description This attribute represents the monetary value of the gross pay calculated for the record. It is mapped to ActivityAmount to enable cost-based process analysis. Analyzing the Gross Pay Amount helps in the Gross To Net Calculation Velocity dashboard. While the dashboard primarily measures time, correlating time against the complexity (and value) of the payment can reveal if high-value or complex commission calculations are the source of performance issues. Why it matters Enables value-stream analysis and outlier detection. Where to get Payroll Result or Pay Register tables Examples 2500.0010500.50480.00
	Has Audit Exception HasAuditException	Flag indicating if an audit exception was triggered.
Description This boolean attribute flags whether the Audit Exception Flagged activity ever occurred for this case. It supports the First Pass Payroll Accuracy Rate KPI. It allows analysts to quickly separate 'clean' cases from those that required intervention, simplifying the analysis of rework causes in the Audit Exception and Correction Trends dashboard. Why it matters Identifies cases requiring intervention. Where to get Derived from existence of 'Audit Exception Flagged' activity Examples truefalse
	Is Off Cycle IsOffCycle	Flag indicating if the payroll run is outside the standard schedule.
Description This boolean attribute identifies whether the payroll record belongs to an off-cycle run. It is used to calculate the Off Cycle Payroll Volume KPI. Off-cycle runs are typically costlier and more manual. Filtering the Process Variant Path Analysis dashboard by this flag highlights the non-standard paths taken to correct errors or issue ad-hoc payments. Why it matters Key filter for analyzing process deviations and rework. Where to get Payroll Header 'Check Date' vs 'Period End Date' logic Examples truefalse
	Is SLA Breached IsSlaBreached	Flag indicating if the payment was executed after the deadline.
Description This boolean attribute is a calculated metric that compares the 'Payment Executed' timestamp with the 'SLA Deadline'. It is the direct driver for the Payroll SLA Adherence Rate KPI. Having this pre-calculated allows for instant filtering of the dashboard to show only problem cases, facilitating root cause analysis on why deadlines were missed. Why it matters KPI driver for compliance monitoring. Where to get Calculated: PaymentTime > SlaDeadline Examples truefalse
	Pay Group PayGroup	The logical grouping of employees for payroll processing.
Description Pay Group is a fundamental configuration in UKG Pro that dictates the frequency (weekly, bi-weekly) and processing rules for a set of employees. It acts as the primary batch identifier. This attribute is critical for the Payroll Cycle Time Distribution dashboard. It allows for the comparison of processing performance between different groups, such as Executive Payroll versus Hourly Plant Workers, identifying if specific configurations are causing systemic lags. Why it matters Primary dimension for grouping and comparing payroll performance. Where to get Payroll Header or Pay Group Configuration table Examples US-BiWeeklyCA-WeeklyExec-Monthly
	Pay Period End Date PayPeriodEndDate	The last day of the pay period being processed.
Description This attribute marks the closing date of the pay cycle. It serves as a critical reference point for determining if submissions are late. It is used alongside the StartTime of the 'Time Sheet Submitted' activity to determine lag times and is a key grouper for the Payroll Cycle Time Distribution dashboard. Why it matters Temporal anchor for the payroll cycle. Where to get Payroll Header or Time Period Configuration Examples 2023-09-302023-10-15
	Payroll Specialist PayrollSpecialist	The user ID or name of the person processing the record.
Description This attribute identifies the specific payroll administrator or specialist responsible for approving the record, performing data corrections, or executing the payment run. It is mapped to the Generic User attribute. This data is vital for the Specialist Workload and Throughput dashboard. It allows management to visualize how work is distributed across the team and identify if specific individuals are overburdened or acting as bottlenecks during the approval phase. Why it matters Enables resource analysis and workload balancing insights. Where to get Audit logs or 'ModifiedBy' columns in transaction tables Examples jsmithmdoesystem_admin
	SLA Deadline SlaProcessingDeadline	The target date/time for payment execution completion.
Description This attribute defines the internal or external deadline for when the payroll process must be completed to ensure timely bank transfers. It is the core attribute for the SLA Compliance and Deadline Monitor dashboard. Comparing the actual Payment Executed timestamp against this deadline allows for the calculation of on-time performance rates and helps prioritize at-risk records. Why it matters Reference point for calculating SLA adherence. Where to get Pay Calendar or derived from Pay Date minus bank processing days Examples 2023-10-13T16:00:00Z2023-10-28T16:00:00Z
	Tax Jurisdiction TaxJurisdiction	The primary state or locality for tax filing.
Description This attribute identifies the main tax jurisdiction associated with the payroll record. It is essential for the Multi State Tax Filing Timelines dashboard. By analyzing process flows based on Tax Jurisdiction, compliance teams can spot if specific states have consistently slower filing completion times or if multi-state employees trigger more audit exceptions than single-state employees. Why it matters Critical for compliance monitoring and geographic analysis. Where to get Tax Location or Employee Tax tables Examples CANYTX
	Correction Category CorrectionCategory	The type of data correction performed (e.g., Time, Rate, Deduction).
Description When a Data Correction Performed activity occurs, this attribute captures the nature of the fix. It is vital for the Manual Data Correction Rate KPI. Understanding if corrections are mostly related to 'Time Entry' versus 'Benefit Deduction' allows the business to target specific upstream systems or teams for process improvement. Why it matters Provides granularity on rework reasons. Where to get Audit Log 'Field Changed' column Examples Time Entry AdjustmentRetroactive PayTax Code Update
	Employee Type EmployeeType	Categorization of employee (e.g., Full-time, Part-time, Contractor).
Description This attribute categorizes the individual associated with the payroll record. It is used in the Time Tracking Approval Performance dashboard. Different employee types often have different time sheet submission behaviors and approval workflows. Segmenting by this attribute helps distinguish between systemic process issues and behavioral patterns specific to certain workforce segments. Why it matters Segments analysis by workforce category. Where to get Employee Master table Examples Full TimePart TimeContractor
	Incentive Source IncentiveSource	Origin of incentive data (e.g., SalesForce, Excel Import).
Description This attribute identifies the source of any incentive or commission data imported into the payroll record. It supports the Incentive Data Import Accuracy dashboard. By correlating this attribute with the Incentive Data Rework Frequency KPI, the team can determine if specific upstream files (e.g., the Northeast Region Sales Report) are consistently prone to formatting errors or data quality issues. Why it matters Traces quality issues back to external data providers. Where to get Import Log filename or Batch ID description Examples Sales Commission FeedManual Bonus UploadExecutive Comp System

Required Recommended Optional

Payroll Processing Activities

These are the key process steps and milestones to capture in your event log to ensure accurate process discovery and bottleneck identification.

4 Recommended 11 Optional

	Activity	Description
	Payment Executed	The effective date or actual transfer of funds to the employee. This marks the fulfillment of the compensation obligation.
Why it matters Used to validate 'SLA Compliance' and ensure employees are paid on the committed date. Where to get Use the 'Check Date' or 'Advice Date' field on the finalized Pay Header record. Capture Logged when transaction payment_post executed Event type explicit
	Payroll Record Approved	The final sign-off on the individual record or the entire pay group. This action locks the record from further changes and queues it for payment generation.
Why it matters A critical milestone separating the working phase from the finalized phase. Used to calculate 'Bank Transfer File Lead Time'. Where to get Capture the status change of the Pay Group or individual Check record to 'Approved' or 'Locked' in the Pay Period Control table. Capture Logged when transaction approve_pay_group executed Event type explicit
	Payroll Record Initialized	The creation of the specific pay line item for an employee within a new pay group instance. This signals that the employee is active and attached to the current processing cycle.
Why it matters Marks the official start of the payroll processing phase within the core system. Essential for distinguishing between time capture duration and actual payroll processing duration. Where to get Identify the timestamp when the record is inserted into the Employee Pay or Check Header table for the specific Pay Date. Capture Logged when transaction pay_period_create executed Event type explicit
	Tax Filing Completed	The successful submission of tax data to the relevant jurisdictions (federal, state, local). This often happens post-payment.
Why it matters Essential for the 'Multi State Tax Filing Timelines' dashboard to ensure regulatory compliance and avoid penalties. Where to get Capture the status update in the Tax Filing Interface or Payment Services log indicating 'Filed' or 'Accepted'. Capture Logged when transaction tax_file_transmit executed Event type explicit
	Audit Exception Flagged	The system or a user identifies a discrepancy, such as negative pay, missing tax codes, or SLA warnings. This puts the record into a state requiring attention.
Why it matters Directly feeds the 'Audit Exception and Correction Trends' dashboard. High volumes here indicate upstream data quality problems. Where to get Identify records in the System Warning Log or Pay Period messages table associated with specific employee IDs. Capture Logged when transaction validation_warning created Event type explicit
	Bank Transfer File Generated	The technical generation of the NACHA or direct deposit file for transmission to the bank. This prepares the funds for movement.
Why it matters Delays here directly risk missing banking cutoffs. Supports the 'Bank Transfer Generation Speed' dashboard. Where to get Capture the timestamp when the ACH/Direct Deposit file creation job completes in the System Job Log. Capture Logged when transaction create_ach_file executed Event type explicit
	Benefits Deductions Applied	The system applies pre-tax and post-tax benefit deductions (health, 401k) to the gross pay. This logic typically runs immediately following gross pay determination.
Why it matters Errors here often require manual corrections. Isolating this step helps determine if delays are caused by the benefits engine or configuration issues. Where to get Inferred from the timestamp of the calculation batch or by observing creation timestamps in the Employee Deduction History table. Capture Derive from comparing field calculation_stage Event type inferred
	Data Correction Performed	A manual modification made to the payroll record (e.g., adjusting hours, overriding tax) after the initial calculation but before final approval.
Why it matters This is the primary measure of rework. Tracking this enables the 'Manual Data Correction Rate' KPI. Where to get Capture updates to the Employee Pay Detail or Deduction tables in the Audit Log where the User ID is not 'System'. Capture Logged when transaction update_pay_detail executed Event type explicit
	Gross Pay Calculated	The initial calculation run where the system determines total earnings based on hours, rates, and incentive data. This occurs before deductions and taxes are applied.
Why it matters Measuring the time from here to 'Taxes Calculated' provides the 'Gross to Net Calculation Velocity' metric required for system performance analysis. Where to get Inferred from the 'Start Time' of the calculation batch process in the System Job Log. Capture Compare status field before/after calculation job start Event type inferred
	Incentive Data Imported	The ingestion of external compensation data such as commissions, bonuses, or one-time payments. This is distinct from regular hours and often involves batch file uploads.
Why it matters High failure rates or rework following this activity indicate issues with data mapping or external file quality, a common source of payroll delays. Where to get Capture from the System Log or Batch Import History where the file type relates to 'Incentives' or 'Additional Pay'. Capture Logged when transaction import_batch_data executed Event type explicit
	Pay Slip Published	The pay statement becomes visible to the employee in the self-service portal. This completes the communication loop.
Why it matters While not a blocking technical step, late publication drives helpdesk calls and impacts employee satisfaction. Where to get Inferred from the 'Check Date' or a specific 'Self Service Release Date' setting in the Pay Group configuration. Capture Derive from comparing field check_date to release_policy Event type inferred
	Payroll Result Previewed	A user opens the payroll register or preview report to validate the calculated results. This represents the transition from automated processing to human review.
Why it matters Indicates the start of the validation phase. A long gap between Calculation and Preview suggests resource availability issues. Where to get Capture from the Audit Log where a user accesses the 'Payroll Register' or 'Pre-Check' report. Capture Logged when transaction report_view_preview executed Event type explicit
	Taxes Calculated	The final stage of the calculation engine where multi-state tax logic is applied to determine net pay. This completes the automated computation phase.
Why it matters Completes the 'Gross to Net' sequence. Long durations here suggest performance issues with the tax engine or complex multi-jurisdiction configurations. Where to get Inferred from the 'End Time' of the calculation batch process in the System Job Log or the timestamp on the Employee Tax table. Capture Compare status field before/after calculation job end Event type inferred
	Time Sheet Approved	The managerial approval of the submitted hours, validating them for payment processing. This step unlocks the data for import into the payroll calculation engine.
Why it matters Bottleneck analysis of this step reveals delays caused by management review, which directly impacts the available window for payroll specialists to process data. Where to get Capture from Time Management history where Status changes to 'Approved' or 'Signed Off'. Capture Logged when transaction time_card_approve executed Event type explicit
	Time Sheet Submitted	The event where an employee or manager submits the time card for the pay period. This marks the entry of raw hours data into the broader payroll workflow, though it may originate in the Time Management module before flowing to core Payroll.
Why it matters Establishes the earliest start timestamp for the end-to-end payroll cycle. Critical for measuring the latency between work performance and payroll data ingestion. Where to get Capture from the Time Management Audit Log or Time Card History table where the Status field changes to 'Submitted'. Capture Logged when transaction time_card_submit executed Event type explicit

Recommended Optional

Extraction Guides

How to get your data from UKG Pro

Steps

Log in to UKG Pro with an account that has Business Intelligence (BI) Authoring permissions.
Navigate to Administration, then select Business Intelligence to launch IBM Cognos Analytics.
Create a new Report and select the Blank template. Choose the List visualization to begin.
You will need to add Data Modules. Because the data spans different domains, you must create a multi-query structure. Go to the Query Explorer view in Cognos.
Create 15 separate Query subjects, one for each activity listed (e.g., Query_TimeSubmit, Query_PayCalc). Map the source packages for each: Time Management for time activities, Payroll for calculation/payment activities, and System Audit for modifications and approvals.
For each Query subject, drag the relevant timestamps and identifiers into the Data Items pane. You must create a calculated data item called ActivityName for each query with a hardcoded string (e.g., 'Time Sheet Submitted').
Ensure every query outputs the exact same columns: PayrollRecordId (concatenate EmployeeID and PayDate), ActivityName, EventTimestamp, and the other required attributes. Use 0 or NULL for metrics not relevant to specific steps to ensure column alignment.
Create a Union Query in the Query Explorer. Drag all 15 individual queries into this Union Query. This performs the 'UNION ALL' operation to stack the data vertically.
Return to the Report Page design view. Point the List object to the Union Query you just created.
Add a filter to the report to restrict the 'Pay Period End Date' to your desired extraction window (e.g., Last 90 Days) to manage report performance.
Run the report in HTML format first to validate the data rows. Check that columns align correctly across the different activity types.
Save the report as 'ProcessMind_Extraction_Report'. Schedule this report to run weekly and deliver the output as a CSV file to your SFTP server for ProcessMind ingestion.

Configuration

Data Packages: Requires access to Payroll, Time Management, and System Audit data packages within UKG Business Intelligence.
Permissions: The user running the report must have security access to view sensitive payroll data (Gross Pay) and audit logs.
Date Range: Recommended to filter by 'Pay Period End Date' rather than 'Transaction Date' to keep full case histories intact. Start with a rolling 6-month window.
Identifier Construction: The Case ID (PayrollRecordId) must be consistent. Use a concatenation of Employee Number and Pay Period End Date (format: EMP123-20231031) to uniquely identify the cycle.
Performance: The System Audit tables can be very large. Apply strict date filters on the Audit queries specifically to prevent timeouts.
Time Zones: UKG Pro often stores times in UTC or the server time. Verify the offset and apply a calculation (e.g., _add_hours) if local time is required for the event log.

a Sample Query config

/* 
   UKG PRO COGNOS ANALYTICS - REPORT SPECIFICATION LOGIC 
   Language: Cognos Expression / Pseudo-SQL Configuration
   NOTE: This logic represents the 15 segments required in the Union Query.
   Each block represents a separate Query Subject in Cognos that must be Unioned.
*/

/* 1. Time Sheet Submitted */
SELECT
  ([TimeMgmt].[EmployeeID] + '-' + [TimeMgmt].[PayPeriodEnd]) AS PayrollRecordId,
  'Time Sheet Submitted' AS ActivityName,
  [TimeMgmt].[Timecard_Submission_Date] AS EventTimestamp,
  'UKG Time' AS SourceSystem,
  [TimeMgmt].[Last_Updated] AS LastUpdateDate,
  [TimeMgmt].[Approver_ID] AS PayrollSpecialist,
  [TimeMgmt].[Gross_Pay_Est] AS GrossPayAmount,
  [TimeMgmt].[Department] AS DepartmentCode,
  [TimeMgmt].[PayGroup] AS PayGroup
FROM [Time Management Package]
WHERE [TimeMgmt].[Status] = 'Submitted'

UNION ALL

/* 2. Time Sheet Approved */
SELECT
  ([TimeMgmt].[EmployeeID] + '-' + [TimeMgmt].[PayPeriodEnd]) AS PayrollRecordId,
  'Time Sheet Approved' AS ActivityName,
  [TimeMgmt].[Timecard_Approval_Date] AS EventTimestamp,
  'UKG Time' AS SourceSystem,
  [TimeMgmt].[Last_Updated] AS LastUpdateDate,
  [TimeMgmt].[Manager_ID] AS PayrollSpecialist,
  [TimeMgmt].[Gross_Pay_Est] AS GrossPayAmount,
  [TimeMgmt].[Department] AS DepartmentCode,
  [TimeMgmt].[PayGroup] AS PayGroup
FROM [Time Management Package]
WHERE [TimeMgmt].[Status] = 'Approved'

UNION ALL

/* 3. Payroll Record Initialized */
SELECT
  ([PayRegister].[EmployeeID] + '-' + [PayRegister].[PeriodEndDate]) AS PayrollRecordId,
  'Payroll Record Initialized' AS ActivityName,
  [PayRegister].[Record_Creation_Date] AS EventTimestamp,
  'UKG Payroll' AS SourceSystem,
  [PayRegister].[Last_Mod_Date] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  0 AS GrossPayAmount,
  [PayRegister].[Home_Dept] AS DepartmentCode,
  [PayRegister].[PayGroup] AS PayGroup
FROM [Payroll Data Package]

UNION ALL

/* 4. Incentive Data Imported */
SELECT
  ([PayDetail].[EmployeeID] + '-' + [PayDetail].[PeriodEndDate]) AS PayrollRecordId,
  'Incentive Data Imported' AS ActivityName,
  [PayDetail].[Import_Date] AS EventTimestamp,
  'UKG Payroll' AS SourceSystem,
  [PayDetail].[Import_Date] AS LastUpdateDate,
  [PayDetail].[User_ID] AS PayrollSpecialist,
  [PayDetail].[Amount] AS GrossPayAmount,
  [PayDetail].[Department] AS DepartmentCode,
  [PayDetail].[PayGroup] AS PayGroup
FROM [Payroll Detail Package]
WHERE [PayDetail].[Source_Type] = 'Import' AND [PayDetail].[Earn_Ded_Type] = 'Earning'

UNION ALL

/* 5. Gross Pay Calculated */
SELECT
  ([PayHistory].[EmployeeID] + '-' + [PayHistory].[PeriodEndDate]) AS PayrollRecordId,
  'Gross Pay Calculated' AS ActivityName,
  [PayHistory].[Calculation_Time] AS EventTimestamp,
  'UKG Calc Engine' AS SourceSystem,
  [PayHistory].[Calculation_Time] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  [PayHistory].[Total_Gross] AS GrossPayAmount,
  [PayHistory].[Department] AS DepartmentCode,
  [PayHistory].[PayGroup] AS PayGroup
FROM [Payroll History Package]

UNION ALL

/* 6. Benefits Deductions Applied */
SELECT
  ([PayHistory].[EmployeeID] + '-' + [PayHistory].[PeriodEndDate]) AS PayrollRecordId,
  'Benefits Deductions Applied' AS ActivityName,
  _add_seconds([PayHistory].[Calculation_Time], 5) AS EventTimestamp,
  'UKG Calc Engine' AS SourceSystem,
  [PayHistory].[Calculation_Time] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  [PayHistory].[Total_Gross] AS GrossPayAmount,
  [PayHistory].[Department] AS DepartmentCode,
  [PayHistory].[PayGroup] AS PayGroup
FROM [Payroll History Package]
WHERE [PayHistory].[Total_Deductions] > 0

UNION ALL

/* 7. Taxes Calculated */
SELECT
  ([PayHistory].[EmployeeID] + '-' + [PayHistory].[PeriodEndDate]) AS PayrollRecordId,
  'Taxes Calculated' AS ActivityName,
  _add_seconds([PayHistory].[Calculation_Time], 10) AS EventTimestamp,
  'UKG Tax Engine' AS SourceSystem,
  [PayHistory].[Calculation_Time] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  [PayHistory].[Total_Gross] AS GrossPayAmount,
  [PayHistory].[Department] AS DepartmentCode,
  [PayHistory].[PayGroup] AS PayGroup
FROM [Payroll History Package]
WHERE [PayHistory].[Total_Taxes] > 0

UNION ALL

/* 8. Payroll Result Previewed */
SELECT
  ([AuditLog].[Target_EmployeeID] + '-' + [AuditLog].[Context_Date]) AS PayrollRecordId,
  'Payroll Result Previewed' AS ActivityName,
  [AuditLog].[Access_Time] AS EventTimestamp,
  'UKG Audit' AS SourceSystem,
  [AuditLog].[Access_Time] AS LastUpdateDate,
  [AuditLog].[User_Name] AS PayrollSpecialist,
  0 AS GrossPayAmount,
  [AuditLog].[Department] AS DepartmentCode,
  [AuditLog].[PayGroup] AS PayGroup
FROM [System Audit Package]
WHERE [AuditLog].[Action] = 'View Report' AND [AuditLog].[Report_Name] LIKE '%Pay Register%'

UNION ALL

/* 9. Audit Exception Flagged */
SELECT
  ([PayMessages].[EmployeeID] + '-' + [PayMessages].[PeriodEndDate]) AS PayrollRecordId,
  'Audit Exception Flagged' AS ActivityName,
  [PayMessages].[Message_Time] AS EventTimestamp,
  'UKG Payroll' AS SourceSystem,
  [PayMessages].[Message_Time] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  0 AS GrossPayAmount,
  [PayMessages].[Department] AS DepartmentCode,
  [PayMessages].[PayGroup] AS PayGroup
FROM [Payroll Messages Package]
WHERE [PayMessages].[Severity] IN ('Warning', 'Error')

UNION ALL

/* 10. Data Correction Performed */
SELECT
  ([AuditData].[EmployeeID] + '-' + [AuditData].[Target_Period_End]) AS PayrollRecordId,
  'Data Correction Performed' AS ActivityName,
  [AuditData].[Change_Time] AS EventTimestamp,
  'UKG Audit' AS SourceSystem,
  [AuditData].[Change_Time] AS LastUpdateDate,
  [AuditData].[User_Changed_By] AS PayrollSpecialist,
  0 AS GrossPayAmount,
  [AuditData].[Department] AS DepartmentCode,
  [AuditData].[PayGroup] AS PayGroup
FROM [Data Audit Package]
WHERE [AuditData].[Table_Name] = 'PayData' AND [AuditData].[Operation] = 'Update'

UNION ALL

/* 11. Payroll Record Approved */
SELECT
  ([PayControl].[EmployeeID] + '-' + [PayControl].[PeriodEndDate]) AS PayrollRecordId,
  'Payroll Record Approved' AS ActivityName,
  [PayControl].[Approval_Time] AS EventTimestamp,
  'UKG Payroll' AS SourceSystem,
  [PayControl].[Approval_Time] AS LastUpdateDate,
  [PayControl].[Approver_ID] AS PayrollSpecialist,
  [PayControl].[Final_Gross] AS GrossPayAmount,
  [PayControl].[Department] AS DepartmentCode,
  [PayControl].[PayGroup] AS PayGroup
FROM [Payroll Control Package]
WHERE [PayControl].[Status] = 'Finalized'

UNION ALL

/* 12. Bank Transfer File Generated */
SELECT
  ([AchFile].[EmployeeID] + '-' + [AchFile].[PeriodEndDate]) AS PayrollRecordId,
  'Bank Transfer File Generated' AS ActivityName,
  [AchFile].[File_Creation_Timestamp] AS EventTimestamp,
  'UKG Banking' AS SourceSystem,
  [AchFile].[File_Creation_Timestamp] AS LastUpdateDate,
  [AchFile].[Generated_By] AS PayrollSpecialist,
  [AchFile].[Net_Pay] AS GrossPayAmount,
  [AchFile].[Department] AS DepartmentCode,
  [AchFile].[PayGroup] AS PayGroup
FROM [Banking / ACH Package]

UNION ALL

/* 13. Payment Executed */
SELECT
  ([CheckRegister].[EmployeeID] + '-' + [CheckRegister].[PeriodEndDate]) AS PayrollRecordId,
  'Payment Executed' AS ActivityName,
  [CheckRegister].[Check_Date] AS EventTimestamp,
  'UKG Payment' AS SourceSystem,
  [CheckRegister].[Check_Date] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  [CheckRegister].[Gross_Amount] AS GrossPayAmount,
  [CheckRegister].[Department] AS DepartmentCode,
  [CheckRegister].[PayGroup] AS PayGroup
FROM [Check Register Package]

UNION ALL

/* 14. Pay Slip Published */
SELECT
  ([CheckRegister].[EmployeeID] + '-' + [CheckRegister].[PeriodEndDate]) AS PayrollRecordId,
  'Pay Slip Published' AS ActivityName,
  [CheckRegister].[Advice_Available_Date] AS EventTimestamp,
  'UKG Self Service' AS SourceSystem,
  [CheckRegister].[Advice_Available_Date] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  0 AS GrossPayAmount,
  [CheckRegister].[Department] AS DepartmentCode,
  [CheckRegister].[PayGroup] AS PayGroup
FROM [Check Register Package]
WHERE [CheckRegister].[Is_Void] = 'False'

UNION ALL

/* 15. Tax Filing Completed */
SELECT
  ([TaxHistory].[EmployeeID] + '-' + [TaxHistory].[PeriodEndDate]) AS PayrollRecordId,
  'Tax Filing Completed' AS ActivityName,
  [TaxHistory].[Filing_Submission_Date] AS EventTimestamp,
  'UKG Tax' AS SourceSystem,
  [TaxHistory].[Last_Update] AS LastUpdateDate,
  'System' AS PayrollSpecialist,
  0 AS GrossPayAmount,
  [TaxHistory].[Department] AS DepartmentCode,
  [TaxHistory].[PayGroup] AS PayGroup
FROM [Tax Filing Package]
WHERE [TaxHistory].[Status] = 'Filed'

Steps

Prerequisites and Authentication: Obtain UKG Pro Web Services API credentials, including a Client ID, Client Secret, and API Key from your UKG Pro administrator. Ensure the associated service account has permissions for the Payroll and Audit API scopes, specifically for endpoints like /payroll/pay-history/pay-summaries, /payroll/pay-statements, and /platform/v1/audit/logs.
Setup Python Environment: Install Python on your machine. Install the necessary libraries for making API requests and handling data by running pip install requests pandas in your terminal.
Create the Python Script: Save the provided Python code from the 'query' section into a file named extract_ukg_payroll.py. Create a .env file in the same directory to securely store your API credentials, or configure them as environment variables on your system.
Configure Script Parameters: Open the script and modify the placeholder values. Set the API_BASE_URL to your organization's UKG Pro instance URL. Adjust the START_DATE and END_DATE variables to define the desired extraction period, for example, the last three to six months.
Execute the Script: Run the script from your terminal using the command python extract_ukg_payroll.py. The script will authenticate, fetch data from the relevant UKG Pro endpoints, and handle pagination automatically.
Data Fetching and Transformation: The script first retrieves an access token. It then fetches payroll summary data and audit logs within the specified date range. It iterates through these records to construct a list of events corresponding to the required activities.
Generate Activity Rows: For each payroll record, the script generates distinct rows for each of the 15 activities. It maps API data fields, such as status changes and timestamps, to specific activities like 'Gross Pay Calculated', 'Payroll Record Approved', and 'Payment Executed'.
Calculate Derived Attributes: After creating the initial event log, the script calculates additional attributes. It determines the CycleTimeDays between payroll initialization and payment, and sets the IsSlaBreached flag based on the payment date versus the SLA deadline.
Export the Event Log: The script consolidates all generated events into a pandas DataFrame and saves it as a CSV file named ukg_payroll_event_log.csv. This file is formatted for direct upload into ProcessMind.
Review and Upload: Open the generated CSV file to review the data for completeness and accuracy. Once validated, upload the file to your ProcessMind project to begin your process mining analysis.

Configuration

Prerequisites: A UKG Pro service account with API access is required. The account must have read permissions for the /payroll/ and /platform/v1/audit/ scopes.
API Credentials: You must provide the following credentials as environment variables or directly in the script: Client ID, Client Secret, API Key, and the API Hostname (Base URL).
Date Range: The script requires a START_DATE and END_DATE to be configured. For initial analysis, a range of 3 to 6 months is recommended to balance data volume with performance.
Filtering: The script can be customized to filter by specific parameters such as companyId or payGroup within the API request URLs to limit the extraction to relevant employee populations.
Pagination Handling: The script is built to handle API pagination automatically, ensuring that all records within the specified date range are retrieved, even if they exceed the single page limit (typically 100 records per call).
Endpoint Dependencies: The extraction quality, especially for workflow activities like approvals and corrections, depends heavily on the availability and richness of the /platform/v1/audit/logs endpoint. Ensure this is enabled and configured to capture relevant events in your UKG Pro instance.

a Sample Query python

import requests
import pandas as pd
import os
import json
from datetime import datetime, timedelta

class=class="hl-string">"hl-comment"># --- Configuration ---
class=class="hl-string">"hl-comment"># Load credentials from environment variables for security
CLIENT_ID = os.environ.get(class="hl-string">'UKG_CLIENT_ID', class="hl-string">'YOUR_CLIENT_ID')
CLIENT_SECRET = os.environ.get(class="hl-string">'UKG_CLIENT_SECRET', class="hl-string">'YOUR_CLIENT_SECRET')
API_KEY = os.environ.get(class="hl-string">'UKG_API_KEY', class="hl-string">'YOUR_API_KEY')
API_BASE_URL = os.environ.get(class="hl-string">'UKG_BASE_URL', class="hl-string">'https://api.ukg.com') class=class="hl-string">"hl-comment"># Adjust if you have a different base URL

class=class="hl-string">"hl-comment"># Set the desired date range for the extraction
START_DATE = class="hl-string">'2023-01-01T00:00:00Z'
END_DATE = class="hl-string">'2023-06-30T23:59:59Z'

def get_access_token():
    class="hl-string">"""Authenticates with UKG Pro and retrieves a bearer token."""
    auth_url = fclass="hl-string">"{API_BASE_URL}/auth/token"
    headers = {class="hl-string">'Content-Type': class="hl-string">'application/json', class="hl-string">'x-api-key': API_KEY}
    payload = {
        class="hl-string">'grant_type': class="hl-string">'client_credentials',
        class="hl-string">'client_id': CLIENT_ID,
        class="hl-string">'client_secret': CLIENT_SECRET,
        class="hl-string">'scope': class="hl-string">'payroll'
    }
    try:
        response = requests.post(auth_url, headers=headers, data=json.dumps(payload))
        response.raise_for_status()
        return response.json().get(class="hl-string">'access_token')
    except requests.exceptions.RequestException as e:
        print(fclass="hl-string">"Error getting access token: {e}")
        return None

def fetch_paginated_data(url, headers):
    class="hl-string">"""Fetches all pages of data from a UKG Pro API endpoint."""
    all_records = []
    while url:
        try:
            response = requests.get(url, headers=headers)
            response.raise_for_status()
            data = response.json()
            all_records.extend(data)

            class=class="hl-string">"hl-comment"># UKG Pro uses a class="hl-string">'Link' header for pagination
            next_link = response.headers.get(class="hl-string">'Link')
            url = None
            if next_link:
                links = next_link.split(class="hl-string">',')
                for link in links:
                    if class="hl-string">'rel="next"' in link:
                        url = link[link.find(class="hl-string">'<')+1:link.find(class="hl-string">'>')]
                        break
        except requests.exceptions.RequestException as e:
            print(fclass="hl-string">"Error fetching data from {url}: {e}")
            break
    return all_records

def main():
    class="hl-string">"""Main function to extract, transform, and save payroll data."""
    token = get_access_token()
    if not token:
        print(class="hl-string">"Failed to authenticate. Exiting.")
        return

    headers = {
        class="hl-string">'Authorization': fclass="hl-string">'Bearer {token}',
        class="hl-string">'x-api-key': API_KEY
    }

    print(class="hl-string">"Fetching payroll history summaries...")
    class=class="hl-string">"hl-comment"># This endpoint provides core pay calculation and payment data.
    class=class="hl-string">"hl-comment"># We filter by payPeriodEndDate for a relevant time slice.
    pay_history_url = fclass="hl-string">"{API_BASE_URL}/v1/payroll/pay-history/pay-summaries?payPeriodEndDate_from={START_DATE}&payPeriodEndDate_to={END_DATE}&per_page=100"
    pay_records = fetch_paginated_data(pay_history_url, headers)

    class=class="hl-string">"hl-comment"># Note: A comprehensive audit log endpoint is assumed for workflow steps.
    class=class="hl-string">"hl-comment"># The exact endpoint and filter parameters may vary. This is a representative example.
    print(class="hl-string">"Fetching audit log data for workflow events...")
    audit_log_url = fclass="hl-string">"{API_BASE_URL}/platform/v1/audit/logs?startTime={START_DATE}&endTime={END_DATE}&per_page=100"
    audit_logs = fetch_paginated_data(audit_log_url, headers)

    class=class="hl-string">"hl-comment"># Process audit logs into a dictionary for easy lookup
    audit_events_by_record = {}
    for log in audit_logs:
        class=class="hl-string">"hl-comment"># Assumption: The audit log contains a reference to the payroll record ID
        record_id = log.get(class="hl-string">'entityId')
        if record_id:
            if record_id not in audit_events_by_record:
                audit_events_by_record[record_id] = []
            audit_events_by_record[record_id].append(log)

    events = []
    print(fclass="hl-string">"Processing {len(pay_records)} payroll records...")
    for record in pay_records:
        payroll_record_id = fclass="hl-string">"{record.get('employeeId')}-{record.get('payPeriodEndDate')}"
        pay_date = datetime.fromisoformat(record.get(class="hl-string">'checkDate').replace(class="hl-string">'Z', class="hl-string">'+00:00'))
        pay_period_end_date = datetime.fromisoformat(record.get(class="hl-string">'payPeriodEndDate').replace(class="hl-string">'Z', class="hl-string">'+00:00'))
        class=class="hl-string">"hl-comment"># Heuristic: Assume initialization happens 1 day after period end
        initialized_ts = pay_period_end_date + timedelta(days=1)
        class=class="hl-string">"hl-comment"># Heuristic: Assume calculation happens 3 days after period end
        calculated_ts = pay_period_end_date + timedelta(days=3)
        
        class=class="hl-string">"hl-comment"># Use a placeholder for SLA deadline, e.g., 1 day before pay date
        sla_deadline = pay_date - timedelta(days=1)

        common_attributes = {
            class="hl-string">'PayrollRecordId': payroll_record_id,
            class="hl-string">'SourceSystem': class="hl-string">'UKG Pro',
            class="hl-string">'PayrollSpecialist': record.get(class="hl-string">'processingUser', class="hl-string">'System'),
            class="hl-string">'DepartmentCode': record.get(class="hl-string">'department'),
            class="hl-string">'CostCenter': record.get(class="hl-string">'costCenter'),
            class="hl-string">'PayGroup': record.get(class="hl-string">'payGroup'),
            class="hl-string">'GrossPayAmount': record.get(class="hl-string">'grossEarnings'),
            class="hl-string">'TaxJurisdiction': record.get(class="hl-string">'primaryTaxState'),
            class="hl-string">'SlaProcessingDeadline': sla_deadline.isoformat(),
            class="hl-string">'IsOffCycle': record.get(class="hl-string">'isOffCycle', False),
            class="hl-string">'PayPeriodEndDate': pay_period_end_date.isoformat(),
            class="hl-string">'HasAuditException': False, class=class="hl-string">"hl-comment"># To be updated by audit events
        }

        class=class="hl-string">"hl-comment"># 1. Time Sheet Submitted (from audit)
        class=class="hl-string">"hl-comment"># 2. Time Sheet Approved (from audit)
        class=class="hl-string">"hl-comment"># These events are highly dependent on audit log content. Using placeholders.
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Time Sheet Submitted', class="hl-string">'EventTimestamp': (initialized_ts - timedelta(hours=12)).isoformat()})
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Time Sheet Approved', class="hl-string">'EventTimestamp': (initialized_ts - timedelta(hours=6)).isoformat()})

        class=class="hl-string">"hl-comment"># 3. Payroll Record Initialized
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Payroll Record Initialized', class="hl-string">'EventTimestamp': initialized_ts.isoformat()})

        class=class="hl-string">"hl-comment"># 4. Incentive Data Imported (from audit)
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Incentive Data Imported', class="hl-string">'EventTimestamp': (initialized_ts + timedelta(days=1)).isoformat()})

        class=class="hl-string">"hl-comment"># 5-7. Calculation Steps
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Gross Pay Calculated', class="hl-string">'EventTimestamp': calculated_ts.isoformat()})
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Benefits Deductions Applied', class="hl-string">'EventTimestamp': (calculated_ts + timedelta(seconds=10)).isoformat()})
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Taxes Calculated', class="hl-string">'EventTimestamp': (calculated_ts + timedelta(seconds=20)).isoformat()})

        class=class="hl-string">"hl-comment"># 8. Payroll Result Previewed (from audit)
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Payroll Result Previewed', class="hl-string">'EventTimestamp': (calculated_ts + timedelta(hours=1)).isoformat()})

        class=class="hl-string">"hl-comment"># 9-10. Audit/Correction Events (from audit log)
        record_audits = audit_events_by_record.get(payroll_record_id, [])
        for audit_event in record_audits:
            event_ts = audit_event.get(class="hl-string">'eventDateTime')
            if class="hl-string">'Exception' in audit_event.get(class="hl-string">'eventName', class="hl-string">''):
                events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Audit Exception Flagged', class="hl-string">'EventTimestamp': event_ts, class="hl-string">'HasAuditException': True})
            if class="hl-string">'Correction' in audit_event.get(class="hl-string">'eventName', class="hl-string">''):
                events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Data Correction Performed', class="hl-string">'EventTimestamp': event_ts})

        class=class="hl-string">"hl-comment"># 11. Payroll Record Approved
        class=class="hl-string">"hl-comment"># Heuristic: Approval happens 2 days before pay date
        approved_ts = pay_date - timedelta(days=2)
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Payroll Record Approved', class="hl-string">'EventTimestamp': approved_ts.isoformat()})

        class=class="hl-string">"hl-comment"># 12. Bank Transfer File Generated
        class=class="hl-string">"hl-comment"># Heuristic: File is generated the day before pay date
        bank_file_ts = pay_date - timedelta(days=1, hours=4)
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Bank Transfer File Generated', class="hl-string">'EventTimestamp': bank_file_ts.isoformat()})
        
        class=class="hl-string">"hl-comment"># 13. Payment Executed
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Payment Executed', class="hl-string">'EventTimestamp': pay_date.isoformat()})

        class=class="hl-string">"hl-comment"># 14. Pay Slip Published
        class=class="hl-string">"hl-comment"># Assumption: Published on the pay date
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Pay Slip Published', class="hl-string">'EventTimestamp': (pay_date + timedelta(hours=8)).isoformat()})

        class=class="hl-string">"hl-comment"># 15. Tax Filing Completed
        class=class="hl-string">"hl-comment"># Heuristic: Filing completed 2 days after pay date
        tax_filed_ts = pay_date + timedelta(days=2)
        events.append({**common_attributes, class="hl-string">'ActivityName': class="hl-string">'Tax Filing Completed', class="hl-string">'EventTimestamp': tax_filed_ts.isoformat()})

    if not events:
        print(class="hl-string">"No events generated. Check API response or date range.")
        return

    class=class="hl-string">"hl-comment"># Create DataFrame and add final attributes
    df = pd.DataFrame(events)
    df[class="hl-string">'EventTimestamp'] = pd.to_datetime(df[class="hl-string">'EventTimestamp'])
    df = df.sort_values(by=[class="hl-string">'PayrollRecordId', class="hl-string">'EventTimestamp']).reset_index(drop=True)

    df[class="hl-string">'LastUpdateDate'] = datetime.now().isoformat()

    class=class="hl-string">"hl-comment"># Calculate cycle time and SLA breach
    start_times = df[df[class="hl-string">'ActivityName'] == class="hl-string">'Payroll Record Initialized'][[class="hl-string">'PayrollRecordId', class="hl-string">'EventTimestamp']].rename(columns={class="hl-string">'EventTimestamp': class="hl-string">'StartTime'})
    end_times = df[df[class="hl-string">'ActivityName'] == class="hl-string">'Payment Executed'][[class="hl-string">'PayrollRecordId', class="hl-string">'EventTimestamp']].rename(columns={class="hl-string">'EventTimestamp': class="hl-string">'EndTime'})
    sla_deadlines = df[[class="hl-string">'PayrollRecordId', class="hl-string">'SlaProcessingDeadline']].drop_duplicates()

    df = df.merge(start_times, on=class="hl-string">'PayrollRecordId', how=class="hl-string">'left')
    df = df.merge(end_times, on=class="hl-string">'PayrollRecordId', how=class="hl-string">'left')
    df = df.merge(sla_deadlines, on=class="hl-string">'PayrollRecordId', how=class="hl-string">'left')

    df[class="hl-string">'CycleTimeDays'] = (df[class="hl-string">'EndTime'] - df[class="hl-string">'StartTime']).dt.total_seconds() / (24 * 3600)
    df[class="hl-string">'IsSlaBreached'] = df[class="hl-string">'EndTime'] > pd.to_datetime(df[class="hl-string">'SlaProcessingDeadline'])
    
    df.drop(columns=[class="hl-string">'StartTime', class="hl-string">'EndTime'], inplace=True)

    class=class="hl-string">"hl-comment"># Reorder columns to match requirements
    final_columns = [
        class="hl-string">'PayrollRecordId', class="hl-string">'ActivityName', class="hl-string">'EventTimestamp', class="hl-string">'SourceSystem', class="hl-string">'LastUpdateDate',
        class="hl-string">'PayrollSpecialist', class="hl-string">'DepartmentCode', class="hl-string">'CostCenter', class="hl-string">'PayGroup', class="hl-string">'GrossPayAmount',
        class="hl-string">'TaxJurisdiction', class="hl-string">'SlaProcessingDeadline', class="hl-string">'IsOffCycle', class="hl-string">'HasAuditException',
        class="hl-string">'PayPeriodEndDate', class="hl-string">'IsSlaBreached', class="hl-string">'CycleTimeDays'
    ]
    df = df[final_columns]

    class=class="hl-string">"hl-comment"># Save to CSV
    output_filename = class="hl-string">'ukg_payroll_event_log.csv'
    df.to_csv(output_filename, index=False, date_format=class="hl-string">'%Y-%m-%dT%H:%M:%S.%fZ')
    print(fclass="hl-string">"Extraction complete. Event log saved to {output_filename}")

if __name__ == class="hl-string">'__main__':
    main()

Your Payroll Processing Data Template

Your Payroll Processing Data Template

Payroll Processing Attributes

Payroll Processing Activities

Extraction Guides

UKG Pro Business Intelligence Report Export

Steps

Configuration

a Sample Query config

UKG Pro Web Services API Python Extraction

Steps

Configuration

a Sample Query python

Ready to Get Started?

Optimize Your UKG Pro Payroll Processing Right Now

Your Payroll Processing Data Template

Your Payroll Processing Data Template

Payroll Processing Attributes

Payroll Processing Activities

Extraction Guides

UKG Pro Business Intelligence Report Export

Steps

Configuration

a Sample Query config

UKG Pro Web Services API Python Extraction

Steps

Configuration

a Sample Query python

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Ready to Get Started?

Optimize Your UKG Pro Payroll Processing Right Now