SayPro Template DCA01 – Data Collection and Analysis

SayPro Template DCA01 – Data Collection and Analysis

Purpose

The DCA01 template ensures clarity and consistency in the data handling process—from collection methods to analysis techniques. It supports:

• Planning of appropriate data collection tools and methods
• Ensuring data integrity and ethical compliance
• Systematic and transparent analysis of findings

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SayPro Template Structure and How to Fill It

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Section 1: Project Overview

• Project Title: Clearly state the research or project title.
• Researcher/Team Name(s): List the main individuals involved in data management.
• Date: Record when the form was completed or last updated.

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Section 2: Data Collection Plan

Data Type	Data Source	Collection Method	Instruments/Tools	Responsible Person	Timeline

Description:

• Data Type: What kind of data? (e.g., qualitative, quantitative, both)
• Data Source: Who or what will provide the data? (e.g., interviews, surveys, documents)
• Collection Method: How will you gather it? (e.g., online survey, face-to-face interview, focus group)
• Instruments/Tools: What tools will you use? (e.g., questionnaire, audio recorder, spreadsheet)
• Responsible Person: Who is in charge of each method?
• Timeline: When will each collection activity occur?

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Section 3: Data Management

• Data Storage Plan:
  Explain where and how the data will be stored securely (e.g., encrypted drives, cloud storage, paper files in locked cabinets).
• Data Privacy & Confidentiality:
  Describe how you will protect sensitive information (e.g., de-identification, password protection, limited access).
• Data Backup Procedures:
  Indicate how often and where data backups will be performed.
• Compliance:
  Note any relevant ethical approvals or data protection regulations (e.g., POPIA, GDPR).

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Section 4: Data Analysis Plan

Data Type	Analysis Method	Software/Tools	Responsible Person	Expected Output

Description:

• Data Type: Specify the kind of data being analyzed.
• Analysis Method: Outline how the data will be analyzed (e.g., thematic analysis, regression analysis, coding, cross-tabulation).
• Software/Tools: List any tools used for analysis (e.g., SPSS, NVivo, Excel, R).
• Responsible Person: Who will conduct the analysis?
• Expected Output: State the result or format of analysis (e.g., charts, tables, themes, insights).

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Section 5: Data Quality and Validation

• Validation Techniques:
  Describe how you will ensure data accuracy and consistency (e.g., triangulation, double entry, peer checking).
• Limitations or Challenges:
  List potential issues that may affect data collection or analysis and how they’ll be addressed.

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Section 6: Ethical Considerations

• Consent Process:
  How will informed consent be obtained from participants?
• Anonymity Measures:
  How will identities be protected in the data and reporting?
• Data Sharing and Retention:
  Indicate if the data will be shared, and how long it will be retained post-project.

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Section 7: Summary and Sign-Off

• Summary of Key Actions:
  Recap major steps or decisions in the data handling process.
• Signatures:
  Space for sign-off from the researcher(s), supervisor(s), or ethics officer.

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SayPro Optional Attachments

• Sample questionnaires or data collection tools
• Data coding framework or rubric
• Charts or mock-ups of expected data displays

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SayPro Example (Abbreviated Table)

Data Collection Table

Data Type	Data Source	Method	Tool	Person	Timeline
Quantitative	100 youth (ages 16–25)	Online survey	Google Forms	J. Mokoena	June 1–15, 2025
Qualitative	10 teachers	Interviews	Audio + guide	R. Dlamini	June 5–10, 2025

Data Analysis Table

Data Type	Method	Software	Responsible	Output
Survey	Descriptive stats	Excel	J. Mokoena	Charts, summary table
Interviews	Thematic analysis	NVivo	R. Dlamini	Coded themes, quotes