Certainly! Below is a SayPro Data Extraction Template designed to collect raw data from SayPro’s platform. This template can be adapted to gather various types of data, such as operational metrics, employee performance, financial data, customer feedback, and more. It includes standard fields to ensure the data is organized, accessible, and usable for analysis.
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SayPro Data Extraction Template Template Version: 1.0Date: [Insert Date]Extracted by: [Data Extraction Team or Individual Name]Reviewed by: [Reviewer Name]Extraction Tool/Method: [Insert tool used, e.g., API, SQL query, manual extraction, etc.]
1. Data Extraction Overview Field Description Example Data Extraction ID Unique identifier for this data extraction DE-2025-01 Extraction Date Date the data was extracted 2025-04-02 Data Source(s) The platform(s) or system(s) from which data was extracted SayPro CRM, Employee Database, etc. Extraction Method How the data was gathered (e.g., manual, automated, API call) SQL query via API Purpose of Extraction Purpose for extracting this data (e.g., operational analysis) Monthly performance review
2. Employee Data Field Description Example Employee ID Unique identifier for the employee E12345 Employee Name Full name of the employee John Doe Department Department to which the employee belongs Sales Role/Title Job title or role of the employee Sales Manager Hire Date Date when the employee was hired 2023-05-01 Employment Status Current status of the employee (e.g., active, on leave) Active Total Hours Worked Total number of hours worked in the extraction period 160 hours Task Completion Rate Percentage of tasks completed by the employee 95% Employee Performance Rating Performance rating based on recent reviews 4.5/5 Training Completed List of training programs completed by the employee Leadership Training, CRM Software Training
3. Operational Data Field Description Example Process ID Unique identifier for the process P98765 Process Name Name or description of the process Customer Onboarding Process Owner Employee or team responsible for the process Sales Team Start Date Date when the process started 2025-03-01 End Date Date when the process was completed or last evaluated 2025-03-25 Total Duration (hours) Total time taken to complete the process 12 hours Cycle Time Average time per cycle of the process 15 minutes Volume of Transactions Total number of transactions processed in the period 500 transactions Error Rate Percentage of errors in the process 2% Process Efficiency Ratio of value-added to non-value-added activities 85%
4. Financial Data Field Description Example Transaction ID Unique identifier for the financial transaction T12567 Transaction Type Type of financial transaction (e.g., revenue, expense) Revenue Amount Amount of money involved in the transaction $5,000 Transaction Date Date the transaction occurred 2025-03-20 Client/Customer ID ID of the client/customer involved in the transaction C12345 Payment Method Method used for the transaction (e.g., credit card, bank transfer) Credit Card Revenue/Expense Category Category of revenue or expense Subscription Fees Profit Margin Profit margin on the transaction 25% Accounts Receivable Outstanding amount from clients or customers $1,200 Accounts Payable Outstanding amount to vendors or suppliers $500
5. Customer Data Field Description Example Customer ID Unique identifier for the customer C00123 Customer Name Full name of the customer Acme Corp. Industry Industry type of the customer Technology Account Manager Employee managing the customer account Jane Smith Account Creation Date Date the customer account was created 2023-08-15 Last Purchase Date Date of the most recent purchase or transaction 2025-03-30 Average Order Value Average value of orders made by the customer $300 Customer Satisfaction Score Customer satisfaction rating (from surveys, feedback) 4.7/5 Churn Risk Probability or indication that the customer will leave Low Risk Customer Lifetime Value (CLV) Total predicted revenue from the customer over their lifetime $50,000
6. System/Platform Data Field Description Example System ID Unique identifier for the system or tool SYS-001 System Name Name of the system or platform SayPro CRM Version Version of the system/platform used 3.2.1 System Downtime (hours) Total downtime of the system during the period 4 hours Error Rate (%) Percentage of errors reported during system usage 0.5% Active Users Number of active users on the system/platform 250 users Data Storage Utilized Amount of storage used by the system 50GB User Access Issues Number of user-reported access issues 3 incidents System Performance Rating Average system performance rating from users 4.8/5
7. Custom Metrics (if applicable) Field Description Example Custom Metric ID Unique identifier for custom metrics CM-001 Metric Name Name of the custom metric Monthly Sales Growth Rate Metric Definition How the metric is calculated (Current Month Sales – Previous Month Sales) / Previous Month Sales Metric Value Value of the metric in the current period 12% Metric Trend Trend of the metric (e.g., increasing, decreasing) Increasing
8. Notes and Observations Field Description Example Additional Notes Any extra observations or insights relevant to the data extraction There was a system upgrade on 2025-03-15 that may have caused the 1-hour downtime. Issues Encountered Any issues or problems faced during data extraction Data was missing for 5 transactions due to API error.
9. Data Validation and Quality Check Field Description Example Data Validation Performed Type of validation checks done (e.g., range checks, duplicates) Duplicate record check, range checks on transaction amounts Validation Results Outcome of validation checks No duplicates found, all transaction amounts within expected range Data Quality Rating Overall quality of the data extracted High Issues Identified Any issues identified during data validation Missing customer address in 3 records
10. Conclusion and Next Steps Field Description Example Next Steps Actions to be taken following this data extraction Review employee performance in light of the data, address missing data in the next extraction Further Analysis Needed Additional analysis required after reviewing the data Investigate the cause of the 2% error rate in the onboarding process
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