SayPro Data Extraction Template: A template for collecting raw data from different departments and sources.

SayPro Data Extraction Template

The SayPro Data Extraction Template is designed to standardize the process of collecting raw data from various departments and sources, ensuring consistency, accuracy, and efficiency. It serves as a structured document or tool that team members can use to input data from diverse platforms, surveys, internal systems, and external sources. This template will help streamline the data collection process and make it easier to later analyze, report, and act on the data.

Here’s an example of what the SayPro Data Extraction Template might look like:

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SayPro Data Extraction Template

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1. General Information

• Report Title: (Provide a clear title for the data being collected)
• Date of Extraction:
  (Date when data is being extracted or collected)
• Prepared By:
  (Name of the person or team preparing the data)
• Department:
  (The department from which the data is being collected, e.g., Marketing, Sales, Customer Support, etc.)
• Data Source(s):
  (List the systems, platforms, surveys, or sources from which the data is coming)
  • Example: CRM system, Customer surveys, Website analytics tools, Internal databases

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2. Key Performance Indicators (KPIs)

Metrics to be Collected: (Adjust as per specific department or project)

Metric Name	Description	Unit of Measurement	Data Source	Data Extraction Method	Frequency of Collection
Customer Satisfaction (CSAT)	Measure of customer satisfaction	Percentage (%)	Customer surveys	Survey responses	Monthly
Net Promoter Score (NPS)	Measures customer loyalty	Score (-100 to 100)	CRM/Survey	Survey distribution	Quarterly
Website Traffic	The number of visits to the website	Number of visits	Google Analytics	Web analytics tool	Daily
Conversion Rate	Percentage of website visitors who take an action	Percentage (%)	Website data	Analytics tool	Weekly
Service Downtime	Time the service is unavailable	Hours	IT Department	Service logs	Monthly
Employee Productivity	Output per employee	Units/Tasks per day	Internal System	Internal time tracking tool	Weekly

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3. Raw Data Collection

Customer Feedback Data (Example: Surveys)

Customer ID	Survey Completion Date	CSAT Rating	NPS Score	Comments
1234	2025-04-01	85%	40	“Great service!”
5678	2025-04-01	60%	25	“Service was slow.”
9101	2025-04-02	90%	50	“Excellent support!”

Operational Data (Example: Service Downtime)

Service	Downtime Date	Downtime Start Time	Downtime End Time	Duration (hours)	Cause
Website	2025-04-01	02:00 AM	03:30 AM	1.5	Server crash
Customer Portal	2025-04-02	10:00 AM	12:00 PM	2	Maintenance
Email Service	2025-04-03	01:00 PM	01:45 PM	0.75	Network issue

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4. Data Validation and Quality Checks

• Data Accuracy: Ensure all data fields are properly filled and formatted.
• Consistency Check: Cross-check data across different sources for consistency (e.g., compare website traffic data from Google Analytics with marketing reports).
• Outliers: Identify and flag any outliers or anomalies in the data (e.g., unusually high/low customer satisfaction scores).
• Data Completeness: Ensure that no critical fields or records are missing, especially in key metrics such as CSAT and NPS scores.

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5. Data Storage & Access

• Storage Location:
  (Where the data is saved—e.g., shared drive, internal database, cloud storage)
• Access Permissions:
  (Who has access to the data and who is authorized to modify it)

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6. Data Analysis Notes

• Preliminary Insights:
  (Any insights or observations that stand out from the raw data, such as an increase in customer satisfaction, a drop in service uptime, etc.)
• Analysis Methodology:
  (Describe the methods used to analyze the data, including any statistical tools, visualization software, or data models applied, e.g., regression analysis, time series analysis, etc.)

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7. Additional Notes

• Potential Data Gaps:
  (Any data that is missing or incomplete, which may affect the analysis)
• Follow-up Actions:
  (What needs to be done next based on the data collected, e.g., further investigation into customer feedback, infrastructure improvements, etc.)

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8. Approval & Sign-Off

Name	Role	Date	Comments
John Doe	Data Analyst	2025-04-03	Data validated and ready for analysis
Jane Smith	Department Head	2025-04-03	Approved for reporting

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Notes for Using the Data Extraction Template:

• Flexibility: This template should be adapted to suit specific departmental needs or different types of data. For instance, marketing might focus more on website metrics, while customer service might prioritize satisfaction and feedback.
• Standardization: Ensure that all data collected is in the same format and standardized across departments. For example, date formats should be consistent, and percentages should be reported in the same decimal places.
• Automation: Whenever possible, integrate automated data collection tools (e.g., Google Analytics, CRM systems, internal databases) to minimize manual entry and reduce errors.
• Security: Follow SayPro’s data security protocols when collecting, storing, and sharing this data, ensuring that sensitive information is protected.

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By using this Data Extraction Template, SayPro ensures that data is collected in a systematic and consistent manner, making it easier for the Monitoring, Evaluation, and Learning (MEL) team to analyze and report on performance. This template is also a key tool for ensuring that relevant data is available for decision-making and strategy development.