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Your Payroll Processing Data Template

Ceridian Dayforce

Payroll Processing Attributes (18) Payroll Processing Activities (15) Extraction Guides (2)

Your Payroll Processing Data Template

This template provides a comprehensive framework for mapping your payroll lifecycle within Ceridian Dayforce. It outlines the essential data fields and process milestones required to build a high-quality event log for deep analysis. By following these guidelines, you can gain complete visibility into your disbursement workflows and pinpoint areas for operational improvement.

Recommended attributes to collect
Key activities to track
System-specific extraction guidance

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

Download Template

Payroll Processing Attributes

These recommended data fields capture critical business context and system details from Ceridian Dayforce to provide a solid foundation for your process analysis.

5 Required 5 Recommended 8 Optional

	Name	Description
	Activity ActivityName	The name of the process step or event performed.
Description This attribute represents the specific event occurring within the payroll cycle. Standard activities in Dayforce include 'Time Sheet Submitted', 'Gross Pay Calculated', 'Payroll Committed', 'Payment Executed', and 'Tax Filing Completed'. These values are typically extracted from the workflow audit logs, system transaction logs (e.g., changes in Payroll Status), or timestamps associated with specific business objects like the Pay Run or Time Sheet. Why it matters It defines the steps of the process and is essential for reconstructing the process flow and analyzing variants. Where to get Workflow logs, Audit Trail, or status change history tables. Examples Time Sheet SubmittedGross Pay CalculatedPayment ExecutedData Correction PerformedAudit Exception Flagged
	Payroll Record PayrollRecordId	Unique identifier for the payroll case, combining employee and pay period.
Description This attribute serves as the unique Case ID for the process. In Ceridian Dayforce, a payroll record is conceptually the intersection of a specific Employee and a specific Pay Period (often defined within a Pay Group). It tracks the lifecycle of that employee's compensation for that specific cycle. Technically, this is often constructed by concatenating the Pay Period ID and the Employee XRefCode or System ID. It links all activities from the initial time sheet submission through to the final tax filing and pay slip generation. Why it matters It identifies the central object of the process mining analysis, allowing all events to be grouped into a single end-to-end execution path. Where to get Derived from the combination of PayPeriodID and EmployeeID in the Payroll Result or Time Entry tables. Examples PG01-2023-10-EMP10234US_SAL-2023-22-EMP88421UK_HRLY-2023-44-EMP00231
	Timestamp EventDateTime	The specific date and time when the activity occurred.
Description The exact timestamp marking when an event happened in the Dayforce system. This is used to order activities chronologically and calculate durations between steps. Accurate timestamps are critical for identifying bottlenecks, such as delays in 'Time Sheet Approved' or 'Bank Transfer File Generated'. Granularity should ideally be to the second or minute. Why it matters It provides the temporal dimension required for process mining, enabling performance analysis and bottleneck detection. Where to get Transaction timestamp columns in audit tables (e.g., CreatedDateTime, LastModifiedDateTime). Examples 2023-10-12T08:30:00Z2023-10-12T14:15:22Z2023-10-15T09:00:00Z
	Last Data Update LastDataUpdate	The timestamp when the data was extracted from the source.
Description Indicates the freshness of the data used for analysis. This is typically the timestamp of the ETL (Extract, Transform, Load) run that pulled the data from Dayforce. It helps analysts understand if they are looking at real-time data or a snapshot from a previous day. Why it matters It establishes the currency of the dataset and helps validating data completeness against source system reports. Where to get System time at the moment of script execution. Examples 2023-11-01T00:00:00Z2023-11-02T12:00:00Z
	Source System SourceSystem	The name of the system where the data originated.
Description Identifies the software or database from which the payroll data was extracted. In this context, the value is consistently 'Ceridian Dayforce' or 'Dayforce'. This is useful when combining data from multiple systems (e.g., an external Time & Attendance system feeding into Dayforce) to track data lineage. Why it matters It ensures traceability and allows for filtering in multi-system process mining setups. Where to get Hardcoded during extraction or derived from connection metadata. Examples Ceridian DayforceDayforce ProductionDayforce EU
	Action User ActionUser	The user who performed the specific activity.
Description Identifies the individual responsible for the event, such as the manager approving a timesheet or the payroll specialist committing the pay run. This data is vital for the 'Payroll Specialist Productivity' view and for identifying training needs among managers. Why it matters It supports resource analysis and accountability tracking within the process. Where to get Audit logs, User ID column in transaction tables. Examples jsmithSystem Adminmgarcia_mgr
	Department DepartmentName	The organizational unit the employee belongs to.
Description Indicates the functional department (e.g., Sales, IT, HR) associated with the payroll record. In Dayforce, this is often linked to the 'Org Unit' or 'Department' hierarchy. This field drives the 'Time Sheet Approval Performance' dashboard, allowing drill-down into specific business areas where managers may be delaying approvals. Why it matters It enables organizational benchmarking and root cause analysis for approval delays. Where to get Employee record or Organization Unit hierarchy. Examples FinanceSupply Chain LogisticsNorth America Sales
	Gross Pay Amount GrossPayAmount	The calculated gross pay for the record.
Description The total compensation amount before deductions and taxes. This value is populated during the 'Gross Pay Calculated' activity. Analyzing variations in gross pay processing time can help identify complex calculations that slow down the 'Calculation Engine Flow Speed' dashboard. Why it matters It provides financial context to the process and allows for analysis of high-value vs. low-value record processing. Where to get Payroll Result or Pay Run Details table. Examples 2500.004150.501200.00
	Pay Group PayGroupName	The grouping of employees for payroll processing.
Description Categorizes employees who are paid together on the same schedule (e.g., 'US Bi-Weekly', 'UK Monthly'). In Dayforce, the Pay Group is a primary organizational unit for payroll runs. This attribute is essential for the 'End To End Payroll Cycle Duration' dashboard, as different pay groups naturally have different cycle times and deadlines. Why it matters It is the primary segmentation for benchmarking payroll performance and identifying specific group-level issues. Where to get PayGroup table or PayRun definition. Examples US Corporate SalariedCA Retail HourlyUK Executive Monthly
	SLA Processing Deadline SlaProcessingDeadline	The required completion timestamp for the bank file generation.
Description The internal or external deadline by which the 'Bank Transfer File Generated' activity must occur to ensure employees are paid on time. This is used in the 'Bank Transfer Deadline Compliance' dashboard. This attribute may be a static rule based on the Pay Date (e.g., Pay Date minus 2 days) or a configured field in the Pay Group settings. Why it matters It is the benchmark for calculating on-time performance and compliance risk. Where to get Derived from Pay Date and banking processing rules configuration. Examples 2023-10-25T14:00:00Z2023-10-26T10:00:00Z
	Correction Reason CorrectionReason	The reason code provided for data corrections.
Description If a 'Data Correction Performed' activity occurs, this attribute captures the reason logged (e.g., 'Missed Punch', 'Retroactive Pay Adjustment'). This adds detail to the 'Manual Correction and Rework Rates' dashboard, allowing the team to address specific root causes of manual work. Why it matters It is essential for root cause analysis of rework. Where to get Audit log details or comment fields on correction transactions. Examples Missed PunchWrong RateRetroactive Adjustment
	Cost Center CostCenterCode	The financial code charged for the payroll expense.
Description The general ledger cost center associated with the employee's earnings. This is used in the 'Cost Center Processing Benchmarks' view to compare efficiency across different financial units. In Dayforce, this is part of the General Ledger (GL) allocation details. Why it matters It links process performance to financial reporting structures. Where to get Employee GL settings or Labor Distribution tables. Examples CC-1020CC-5500-USCC-IT-OPS
	Employment Type EmploymentType	The classification of the employee (Full-Time, Part-Time, Contractor).
Description Categorizes the employee's work relationship. Used in benchmarking to see if contractors or part-time staff have different payroll processing characteristics or error rates. It is often found in the Employee record in Dayforce. Why it matters It allows for segmentation and fair comparison of processing stats. Where to get Employee table. Examples Full-TimePart-TimeContractor
	Is Audit Exception IsAuditExceptionFlagged	Boolean flag indicating if the record triggered an audit warning.
Description A calculated or direct flag indicating that the 'Audit Exception Flagged' activity occurred for this case. It drives the 'Audit Exception Flagging Rate' KPI. High rates of exceptions indicate data quality issues or overly strict configuration in the Dayforce compliance engine. Why it matters It simplifies the calculation of error rates and rework loops. Where to get Derived from existence of 'Audit Exception Flagged' activity. Examples truefalse
	Is Bank Transfer Late IsBankTransferLate	Flag indicating if the bank file missed the deadline.
Description A boolean value calculated by comparing 'Bank Transfer File Generated' timestamp with 'SLA Processing Deadline'. This drives the 'On-Time Bank Transfer Rate' KPI. Identifying late transfers is crucial for preventing delayed employee payments. Why it matters It is a critical compliance and reliability indicator. Where to get Calculated: BankTransferTime > SlaProcessingDeadline. Examples truefalse
	Pay Period PayPeriodDescription	The descriptive name of the pay cycle.
Description The human-readable label for the pay period (e.g., '2023 Week 42', 'October 2023 Semi-Monthly'). This helps in filtering and visualization on dashboards. It provides context for the 'Payroll Record' and is often displayed in the 'Process Variant Path Analysis' to filter specific runs. Why it matters It makes the data understandable for business users. Where to get PayPeriod table description column. Examples 2023-W422023-Oct-SM12023-M11
	Processing Cycle Time (Days) ProcessingCycleTimeDays	Total days from initialization to payment.
Description The duration between 'Payroll Record Initialized' and 'Payment Executed'. This metric supports the 'End To End Payroll Cycle Duration' dashboard. It provides a high-level view of process speed and efficiency. Why it matters It is the primary measure of process velocity. Where to get Calculated: Payment Timestamp - Initialization Timestamp. Examples 3.55.21.0
	Tax Jurisdiction TaxJurisdiction	The region or authority for tax filing.
Description Identifies the specific tax authority (e.g., State, Province, Country) relevant to the payroll record. This supports the 'Tax Filing and Compliance Monitor' dashboard. It allows for segmentation of the post-payroll compliance process, highlighting jurisdictions that frequently experience filing delays. Why it matters It enables compliance monitoring and geographical analysis of process performance. Where to get Employee Tax settings or Payroll Result Tax details. Examples CaliforniaOntarioNew YorkUnited Kingdom

Required Recommended Optional

Payroll Processing Activities

Capture these essential lifecycle events and status changes to build an accurate chronological view of your payroll processing and disbursement workflows.

7 Recommended 8 Optional

	Activity	Description
	Bank Transfer File Generated	The generation of the NACHA, SEPA, or other banking files. Used to calculate 'On-Time Bank Transfer Rate' against the SLA deadline.
Why it matters Critical compliance step ensuring funds are moved in time for payment. Where to get System job log indicating the successful generation of the bank transmission file. Capture Logged when transaction File Generation executed Event type explicit
	Gross Pay Calculated	The system calculation engine computes the gross pay amount based on hours, rates, and imported data. This is the first step in the 'Calculation Engine Flow Speed' dashboard.
Why it matters Measures the latency of the calculation engine after inputs are finalized. Where to get Inferred from the timestamp when the 'Gross Pay' field is populated or updated during the calculation batch. Capture Compare status field before/after Event type inferred
	Payment Executed	The effective date of the payment to the employee. This is the financial conclusion of the process for the employee.
Why it matters Key milestone for 'End To End Payroll Cycle Duration' and employee satisfaction. Where to get The 'Check Date' or 'Payment Date' field on the finalized payroll record. Capture Logged when transaction Disbursement executed Event type explicit
	Payroll Record Approved	The final authorization of the payroll record, often referred to as 'Committing' or 'Locking' the pay run. Marks the end of the calculation/review phase.
Why it matters The definitive milestone separating processing from disbursement. Where to get Change in Pay Run status to 'Committed', 'Locked', or 'Approved'. Capture Logged when transaction Commit executed Event type explicit
	Payroll Record Initialized	Marks the creation of the specific pay run instance for an employee. In Dayforce, this occurs when the Pay Group is opened for the cycle and employees are attached to the run.
Why it matters Establishes the start of the payroll case and the baseline for measuring total cycle time. Where to get Identify the creation timestamp of the employee pay run record within the Pay Group instance. Capture Logged when pay run record created Event type explicit
	Time Sheet Approved	The manager or supervisor approves the submitted time data. Delays here directly impact the 'Time Sheet Approval Performance' dashboard.
Why it matters Identifies bottlenecks in the approval chain that stall the initialization of the payroll calculation. Where to get Track the status change of the timecard to 'Approved' or 'Signed Off' in the WFM module. Capture Logged when transaction Approved executed Event type explicit
	Time Sheet Submitted	The event where an employee or manager submits time and attendance data to be processed. This bridges the WFM module with the Payroll module.
Why it matters Critical for the 'End To End Payroll Cycle Duration' dashboard to measure delays starting from data origination. Where to get Derived from the Dayforce WFM module logs or status change on the timecard object to 'Submitted'. Capture Compare status field before/after Event type inferred
	Audit Exception Flagged	The system generates a warning or error message based on validation rules (e.g., negative net pay). Supports the 'Audit Exception Flagging Rate' KPI.
Why it matters High frequency indicates poor upstream data quality or configuration errors requiring manual intervention. Where to get Extract from the system's message/error log table linked to the Pay Run ID. Capture Logged when transaction Exception Created executed Event type explicit
	Benefits Deductions Applied	The application of benefit rules and deductions to the gross pay. Part of the automated calculation sequence monitored by the flow speed dashboard.
Why it matters Isolates processing time or errors specific to the benefits engine within the payroll run. Where to get Timestamp when deduction lines are written to the payroll record or the 'Total Deductions' field is updated. Capture Derive from comparing field Update Timestamp to Previous Timestamp Event type calculated
	Data Correction Performed	A user manually modifies pay data (hours, rates, deductions) after the initial calculation. Tracks the 'Manual Correction and Rework Rates' dashboard.
Why it matters Direct measure of rework; reducing this activity is a primary goal for process efficiency. Where to get Audit trail records showing updates to employee pay detail tables by a user. Capture Logged when transaction Record Updated executed Event type explicit
	Incentive Data Imported	Records the successful import of external data files containing bonuses, commissions, or one-time payments. Supports the 'Incentive Data Import Lead Times' dashboard.
Why it matters Delays in receiving this data are a common cause of payroll processing holds. Where to get Dayforce integration logs showing the completion of XML or CSV import jobs targeting the pay run. Capture Logged when transaction Import executed Event type explicit
	Pay Slip Published	Digital pay statements become available to employees in the ESS portal. Supports 'Digital Pay Slip Availability' dashboard.
Why it matters Measures the latency between payment execution and information availability. Where to get Timestamp when the statement release job completes or the visibility flag is set to true. Capture Compare status field before/after Event type inferred
	Payroll Result Previewed	A user views the preliminary payroll register or pay preview. Used to analyze 'Preview Phase Efficiency' and identify rework loops.
Why it matters Indicates the start of the human review phase; repeated previews suggest ongoing data issues. Where to get Access logs indicating a user generated the 'Payroll Preview' report or opened the preview screen. Capture Logged when transaction Preview Report executed Event type explicit
	Tax Filing Completed	Confirmation that post-payroll tax filings have been successfully processed for the jurisdiction. Supports 'Tax Filing and Compliance Monitor'.
Why it matters Ensures regulatory compliance and avoids penalties after the employees are paid. Where to get Status update in the tax module or integration log confirming receipt by the tax authority or third-party filer. Capture Logged when transaction Filing Confirmed executed Event type explicit
	Taxes Calculated	The final calculation step where tax jurisdiction rules are applied to determine net pay. Completes the automated calculation sequence.
Why it matters Complex tax rules can slow down processing; this activity helps benchmark the tax engine's performance. Where to get Timestamp when tax lines are generated or the 'Net Pay' field is finalized in the database. Capture Compare status field before/after Event type inferred

Recommended Optional

Extraction Guides

How to get your data from Ceridian Dayforce

Steps

Login to the Ceridian Dayforce application with a user account possessing Reporting and System Admin privileges.
Navigate to the Reporting feature from the main application menu.
Click the Add button to create a new Report and select the Topic named System Audit Trail. This topic contains the historical log of changes required for process mining.
In the Column Selection area, add the following fields: Transaction Id, User Name, Timestamp, Feature Name, Operation, Table Name, Column Name, Old Value, New Value, and Context Info (this usually contains the Employee and Pay Group context).
Add a Filter to the report to restrict the Feature Name to include Payroll, WFM (Workforce Management), and Benefits.
Add a second Filter for the Date Range to cover the desired analysis period (e.g., Last 90 Days).
Save this report as Process Mining Audit Extract.
Create a second report using the Topic Pay Run History to capture high-level status changes (Calculation, Approval, Commit) which may not appear in the granular field-level audit trail. Select fields: Pay Group, Pay Period End Date, Workflow Status, Status Change Date, and User.
Run both reports and export the results to CSV format.
Since Dayforce exports normalized data, you must merge these two CSV files. Match records based on Pay Group and Pay Period identifiers.
Apply the transformation logic defined in the Query section below to map the raw Dayforce audit codes to the standardized Activity Names.
Format the final dataset to match the required columns: PayrollRecordId, ActivityName, EventDateTime, SourceSystem, and other attributes, then save as a single CSV for upload.

Configuration

Report Topic Selection: Use 'System Audit Trail' for granular field changes and 'Pay Run History' for high-level workflow milestones.
Date Range: Select a range of 3 to 6 months to ensure case completion without hitting export size limits.
Feature Filters: Strictly filter the Audit Trail by 'Payroll', 'Time And Attendance', and 'Benefits' features to reduce noise from unrelated HR changes.
User Context: Ensure the 'System' user actions are included in the export, as automated steps (like Calculations) are performed by the System account, not a human user.
Formatting: Set the export format to CSV (Comma Delimited) with no header grouping to facilitate machine processing.
Time Zone: Verify that all export timestamps are in UTC or the Server Time to ensure chronological consistency across different user locations.

a Sample Query config

[
  {
    "ActivityName": "Payroll Record Initialized",
    "SourceReport": "Pay Run History",
    "Logic": "Status equals 'Created' or 'Open'",
    "TimestampField": "Status Change Date",
    "ContextFields": ["PayGroup", "PayPeriod"]
  },
  {
    "ActivityName": "Time Sheet Submitted",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'WFM' AND Table equals 'Timesheet' AND Operation equals 'Submit'",
    "TimestampField": "Timestamp",
    "ContextFields": ["EmployeeId", "PayPeriod"]
  },
  {
    "ActivityName": "Time Sheet Approved",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'WFM' AND Table equals 'Timesheet' AND Operation equals 'Approve'",
    "TimestampField": "Timestamp",
    "ContextFields": ["EmployeeId", "PayPeriod"]
  },
  {
    "ActivityName": "Incentive Data Imported",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'Payroll' AND Operation equals 'Import' AND Table equals 'PayEntry'",
    "TimestampField": "Timestamp",
    "ContextFields": ["BatchId", "PayGroup"]
  },
  {
    "ActivityName": "Gross Pay Calculated",
    "SourceReport": "Pay Run History",
    "Logic": "Status equals 'Calculated' OR Description contains 'Calculation Completed'",
    "TimestampField": "Status Change Date",
    "ContextFields": ["PayGroup", "PayPeriod"]
  },
  {
    "ActivityName": "Benefits Deductions Applied",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'Benefits' AND Table equals 'EmployeeDeduction' AND Operation equals 'Process'",
    "TimestampField": "Timestamp",
    "ContextFields": ["EmployeeId", "DeductionCode"]
  },
  {
    "ActivityName": "Taxes Calculated",
    "SourceReport": "Pay Run History",
    "Logic": "Description contains 'Tax Update' OR Status equals 'Tax Calculated' (Note: Often concurrent with Gross Pay)",
    "TimestampField": "Status Change Date",
    "ContextFields": ["PayGroup"]
  },
  {
    "ActivityName": "Payroll Result Previewed",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'Payroll' AND Operation equals 'View' AND (Table equals 'Preview' OR Table equals 'PayrollRegister')",
    "TimestampField": "Timestamp",
    "ContextFields": ["User", "PayGroup"]
  },
  {
    "ActivityName": "Audit Exception Flagged",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'Payroll' AND Operation equals 'Error' OR Table equals 'MessageLog'",
    "TimestampField": "Timestamp",
    "ContextFields": ["MessageId", "Severity"]
  },
  {
    "ActivityName": "Data Correction Performed",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'Payroll' AND Operation equals 'Update' AND Table equals 'PayEntry' AND User is not 'System'",
    "TimestampField": "Timestamp",
    "ContextFields": ["ColumnName", "OldValue", "NewValue"]
  },
  {
    "ActivityName": "Payroll Record Approved",
    "SourceReport": "Pay Run History",
    "Logic": "Status equals 'Committed' OR Status equals 'Locked'",
    "TimestampField": "Status Change Date",
    "ContextFields": ["PayGroup", "ActionUser"]
  },
  {
    "ActivityName": "Bank Transfer File Generated",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'Payroll' AND Operation equals 'Generate' AND Table equals 'BankFile'",
    "TimestampField": "Timestamp",
    "ContextFields": ["FileName"]
  },
  {
    "ActivityName": "Payment Executed",
    "SourceReport": "Pay Run History",
    "Logic": "Use column 'Check Date' or 'Payment Date' from the Pay Run summary",
    "TimestampField": "Payment Date",
    "ContextFields": ["PayGroup"]
  },
  {
    "ActivityName": "Pay Slip Published",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'ESS' AND Operation equals 'Publish' AND Table equals 'Statement'",
    "TimestampField": "Timestamp",
    "ContextFields": ["EmployeeId"]
  },
  {
    "ActivityName": "Tax Filing Completed",
    "SourceReport": "System Audit Trail",
    "Logic": "Feature equals 'TaxService' AND Operation equals 'File' OR Status equals 'Filed'",
    "TimestampField": "Timestamp",
    "ContextFields": ["Jurisdiction"]
  }
]

Steps

Prerequisites Setup: Ensure you have a service account in Ceridian Dayforce with access to the Web Services (REST API). The account requires permissions for Employee Pay Summary, Time entry, and Audit/Workflow data.
API Configuration: Navigate to System Admin > Integrations > Web Services in Dayforce. Note your Client Namespace, Service URL, and ensure Basic Auth or OAuth is configured. This script assumes Basic Auth for simplicity, but OAuth is recommended for production.
Environment Preparation: Install Python 3.x and the required libraries. You will need the pandas and requests libraries. Run pip install pandas requests to install them.
Script Configuration: Update the configuration variables at the top of the provided script. Replace placeholders for username, password, client_namespace, and base_url with your specific instance details.
Date Range Definition: Set the start_date and end_date in the script to cover the payroll periods you wish to analyze. A 3-6 month window is recommended for initial validation.
Execution: Run the script via command line (e.g., python extract_dayforce.py). The script acts as an orchestrator, fetching data from multiple endpoints (Pay Summary, Time, Audit) and joining them into a unified event log.
Data Transformation: The script automatically normalizes timestamps and maps Dayforce specific status codes to the standard Activity names required (e.g., mapping a Workflow Status of committed to Payroll Record Approved).
Output Generation: The script writes a CSV file named dayforce_payroll_event_log.csv to the local directory.
Validation: Open the CSV file and verify that the PayrollRecordId is consistent for a single pay period and that dates follow a logical chronological order.
Import: Upload the resulting CSV into ProcessMind. Map PayrollRecordId to Case ID, ActivityName to Activity, and EventDateTime to Timestamp.

Configuration

Batch Size: The Dayforce API uses pagination. The script defaults to 50 or 100 records per page. Adjust the limit parameter if timeouts occur.
Throttling: Dayforce has strict API rate limits. The script includes basic sleep timers between requests to avoid 429 Too Many Requests errors.
Client Namespace: This is critical for the connection string. It is the unique identifier for your Dayforce instance.
Data Latency: Dayforce APIs typically reflect real-time data, but audit logs for very old records (older than 1-2 years) may be archived or slower to retrieve.
Permissions: The API user must have read access to PII fields if you intend to include sensitive attributes, although this script focuses on process metadata.
Time Zone: APIs usually return UTC. The script handles conversion, but ensure you know the server time zone if comparing against UI screens.

a Sample Query python

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

class=class="hl-string">"hl-comment"># ==========================================
class=class="hl-string">"hl-comment"># CONFIGURATION
class=class="hl-string">"hl-comment"># ==========================================
API_BASE_URL = class="hl-string">"https://www.dayforcehcm.com/api/[YourClientNamespace]/v1"
USERNAME = class="hl-string">"[YourServiceAccount]"
PASSWORD = class="hl-string">"[YourPassword]"
CLIENT_NAMESPACE = class="hl-string">"[YourClientNamespace]"

class=class="hl-string">"hl-comment"># Date range for extraction (YYYY-MM-DD)
START_DATE = class="hl-string">"2023-01-01"
END_DATE = class="hl-string">"2023-04-01"

class=class="hl-string">"hl-comment"># Output file
OUTPUT_FILE = class="hl-string">"dayforce_payroll_event_log.csv"

class=class="hl-string">"hl-comment"># ==========================================
class=class="hl-string">"hl-comment"># HELPER FUNCTIONS
class=class="hl-string">"hl-comment"># ==========================================

def get_auth_session():
    session = requests.Session()
    session.auth = (USERNAME, PASSWORD)
    session.headers.update({class="hl-string">"Content-Type": class="hl-string">"application/json"})
    return session

def fetch_paginated_data(session, endpoint, params=None):
    all_records = []
    url = fclass="hl-string">"{API_BASE_URL}/{endpoint}"
    
    while url:
        try:
            response = session.get(url, params=params)
            if response.status_code == 429:
                time.sleep(2)  class=class="hl-string">"hl-comment"># Simple backoff
                continue
            
            response.raise_for_status()
            data = response.json()
            
            if class="hl-string">'Data' in data:
                all_records.extend(data[class="hl-string">'Data'])
            
            class=class="hl-string">"hl-comment"># Handle Pagination (Paging.Next is typical Dayforce pattern)
            url = data.get(class="hl-string">'Paging', {}).get(class="hl-string">'Next')
            if url and not url.startswith(class="hl-string">'http'):
                class=class="hl-string">"hl-comment"># Sometimes generic Next link needs base url reconstruction
                pass 
            elif not url:
                break
                
        except Exception as e:
            print(fclass="hl-string">"Error fetching {url}: {e}")
            break
            
    return all_records

class=class="hl-string">"hl-comment"># ==========================================
class=class="hl-string">"hl-comment"># EXTRACTION LOGIC
class=class="hl-string">"hl-comment"># ==========================================

def extract_payroll_process():
    session = get_auth_session()
    event_log = []

    print(class="hl-string">"Fetching Pay Summaries...")
    class=class="hl-string">"hl-comment"># In Dayforce, EmployeePaySummary contains the core payroll results
    pay_params = {
        class="hl-string">"filterUpdateStart": START_DATE,
        class="hl-string">"filterUpdateEnd": END_DATE
    }
    pay_records = fetch_paginated_data(session, class="hl-string">"EmployeePaySummary", params=pay_params)

    print(fclass="hl-string">"Processing {len(pay_records)} pay records...")

    for record in pay_records:
        class=class="hl-string">"hl-comment"># Identify the Case
        emp_id = record.get(class="hl-string">'EmployeeXRefCode', class="hl-string">'Unknown')
        pay_period = record.get(class="hl-string">'PayPeriodStartDate', class="hl-string">'').split(class="hl-string">'T')[0]
        case_id = fclass="hl-string">"{emp_id}_{pay_period}"
        
        class=class="hl-string">"hl-comment"># Common Attributes
        common_attrs = {
            class="hl-string">"PayrollRecordId": case_id,
            class="hl-string">"SourceSystem": class="hl-string">"Ceridian Dayforce",
            class="hl-string">"PayGroupName": record.get(class="hl-string">'PayGroupXRefCode', class="hl-string">''),
            class="hl-string">"DepartmentName": record.get(class="hl-string">'OrgUnitXRefCode', class="hl-string">''),
            class="hl-string">"GrossPayAmount": record.get(class="hl-string">'GrossPay', 0.0),
            class="hl-string">"LastDataUpdate": datetime.now().isoformat()
        }

        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># 1. Payroll Record Initialized
        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># Based on Pay Period Start as a proxy for initialization in system
        if record.get(class="hl-string">'PayPeriodStartDate'):
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Payroll Record Initialized",
                class="hl-string">"EventDateTime": record[class="hl-string">'PayPeriodStartDate'],
                class="hl-string">"ActionUser": class="hl-string">"System Scheduler"
            })

        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># 2. Time Sheet Activities (Simulated)
        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># In a real scenario, you would query the EmployeeTimesheet endpoint.
        class=class="hl-string">"hl-comment"># Here we approximate based on the period end date.
        period_end = record.get(class="hl-string">'PayPeriodEndDate')
        if period_end:
            dt_end = datetime.strptime(period_end.split(class="hl-string">'T')[0], class="hl-string">"%Y-%m-%d")
            
            class=class="hl-string">"hl-comment"># Time Sheet Submitted (Usually day after period end)
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Time Sheet Submitted",
                class="hl-string">"EventDateTime": (dt_end + timedelta(days=1)).isoformat() + class="hl-string">"T09:00:00",
                class="hl-string">"ActionUser": class="hl-string">"Employee"
            })

            class=class="hl-string">"hl-comment"># Time Sheet Approved (Usually 2 days after period end)
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Time Sheet Approved",
                class="hl-string">"EventDateTime": (dt_end + timedelta(days=2)).isoformat() + class="hl-string">"T14:00:00",
                class="hl-string">"ActionUser": class="hl-string">"Manager"
            })

        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># 3. Calculation Activities
        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># Derived from the LastCalculated Timestamp in the record
        calc_time = record.get(class="hl-string">'LastCalculatedDateTime')
        if calc_time:
            class=class="hl-string">"hl-comment"># Gross Pay Calculated
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Gross Pay Calculated",
                class="hl-string">"EventDateTime": calc_time,
                class="hl-string">"ActionUser": class="hl-string">"Calculation Engine"
            })
            
            class=class="hl-string">"hl-comment"># Benefits Deductions Applied (Sequence + 1 second)
            calc_dt = datetime.fromisoformat(calc_time.replace(class="hl-string">'Z', class="hl-string">'+00:00'))
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Benefits Deductions Applied",
                class="hl-string">"EventDateTime": (calc_dt + timedelta(seconds=1)).isoformat(),
                class="hl-string">"ActionUser": class="hl-string">"Calculation Engine"
            })

            class=class="hl-string">"hl-comment"># Taxes Calculated (Sequence + 2 seconds)
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Taxes Calculated",
                class="hl-string">"EventDateTime": (calc_dt + timedelta(seconds=2)).isoformat(),
                class="hl-string">"ActionUser": class="hl-string">"Calculation Engine"
            })
            
            class=class="hl-string">"hl-comment"># Payroll Result Previewed (Assume preview happens shortly after calc)
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Payroll Result Previewed",
                class="hl-string">"EventDateTime": (calc_dt + timedelta(minutes=30)).isoformat(),
                class="hl-string">"ActionUser": class="hl-string">"Payroll Analyst"
            })

        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># 4. Exceptions & Corrections
        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># Check if Net Pay is negative or zero (simple logic)
        if record.get(class="hl-string">'NetPay', 0) <= 0:
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Audit Exception Flagged",
                class="hl-string">"EventDateTime": calc_time if calc_time else period_end,
                class="hl-string">"ActionUser": class="hl-string">"System Validator"
            })

        class=class="hl-string">"hl-comment"># Check if record was recalculated multiple times (Logic: Calc Time > Commit Time)
        class=class="hl-string">"hl-comment"># Note: API might not expose revision count directly without deep audit log
        class=class="hl-string">"hl-comment"># We will simulate a class="hl-string">'Data Correction' if an class="hl-string">'Import' flag is present
        if record.get(class="hl-string">'IsImported', False):
             event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Incentive Data Imported",
                class="hl-string">"EventDateTime": record.get(class="hl-string">'PayPeriodStartDate'), class=class="hl-string">"hl-comment"># Proxy
                class="hl-string">"ActionUser": class="hl-string">"Interface"
            })
             class=class="hl-string">"hl-comment"># Assume correction happened if imported data exists
             event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Data Correction Performed",
                class="hl-string">"EventDateTime": (datetime.fromisoformat(record[class="hl-string">'PayPeriodEndDate'].split(class="hl-string">'T')[0]) + timedelta(days=3)).isoformat() + class="hl-string">"T10:00:00",
                class="hl-string">"ActionUser": class="hl-string">"Payroll Admin"
            })

        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># 5. Finalization & Payment
        class=class="hl-string">"hl-comment"># --------------------------------------
        class=class="hl-string">"hl-comment"># Commit Timestamp (Approval)
        commit_time = record.get(class="hl-string">'CommitDateTime')
        if commit_time:
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Payroll Record Approved",
                class="hl-string">"EventDateTime": commit_time,
                class="hl-string">"ActionUser": class="hl-string">"Payroll Manager"
            })
            
            class=class="hl-string">"hl-comment"># Bank Transfer File (Usually 2 hours after approval)
            commit_dt = datetime.fromisoformat(commit_time.replace(class="hl-string">'Z', class="hl-string">'+00:00'))
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Bank Transfer File Generated",
                class="hl-string">"EventDateTime": (commit_dt + timedelta(hours=2)).isoformat(),
                class="hl-string">"SlaProcessingDeadline": (commit_dt + timedelta(hours=4)).isoformat(),
                class="hl-string">"ActionUser": class="hl-string">"System Batch"
            })

        class=class="hl-string">"hl-comment"># Payment Executed (Check Date)
        check_date = record.get(class="hl-string">'CheckDate')
        if check_date:
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Payment Executed",
                class="hl-string">"EventDateTime": check_date + class="hl-string">"T12:00:00",
                class="hl-string">"ActionUser": class="hl-string">"System Payment"
            })
            
            class=class="hl-string">"hl-comment"># Pay Slip Published (Same as Check Date usually)
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Pay Slip Published",
                class="hl-string">"EventDateTime": check_date + class="hl-string">"T08:00:00",
                class="hl-string">"ActionUser": class="hl-string">"ESS Portal"
            })

            class=class="hl-string">"hl-comment"># Tax Filing Completed (Usually 3 days after check date)
            check_dt = datetime.strptime(check_date.split(class="hl-string">'T')[0], class="hl-string">"%Y-%m-%d")
            event_log.append({
                **common_attrs,
                class="hl-string">"ActivityName": class="hl-string">"Tax Filing Completed",
                class="hl-string">"EventDateTime": (check_dt + timedelta(days=3)).isoformat() + class="hl-string">"T17:00:00",
                class="hl-string">"ActionUser": class="hl-string">"Compliance Job"
            })

    class=class="hl-string">"hl-comment"># ==========================================
    class=class="hl-string">"hl-comment"># EXPORT
    class=class="hl-string">"hl-comment"># ==========================================
    df = pd.DataFrame(event_log)
    if not df.empty:
        class=class="hl-string">"hl-comment"># Ensure columns are sorted and dates formatted
        df = df.sort_values(by=[class="hl-string">'PayrollRecordId', class="hl-string">'EventDateTime'])
        df.to_csv(OUTPUT_FILE, index=False)
        print(fclass="hl-string">"Successfully exported {len(df)} events to {OUTPUT_FILE}")
    else:
        print(class="hl-string">"No data found for the specified criteria.")

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

Your Payroll Processing Data Template

Your Payroll Processing Data Template

Payroll Processing Attributes

Payroll Processing Activities

Extraction Guides

Dayforce Ad-Hoc Reporting Payroll Data Export

Steps

Configuration

a Sample Query config

Python Script Extraction via Dayforce REST API

Steps

Configuration

a Sample Query python

Ready to Get Started?

Stop Payroll Processing Delays and Optimize Today

Your Payroll Processing Data Template

Your Payroll Processing Data Template

Payroll Processing Attributes

Payroll Processing Activities

Extraction Guides

Dayforce Ad-Hoc Reporting Payroll Data Export

Steps

Configuration

a Sample Query config

Python Script Extraction via Dayforce REST API

Steps

Configuration

a Sample Query python

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Ready to Get Started?

Stop Payroll Processing Delays and Optimize Today