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Annex 5 Guidance on good data and record management practices Background During an informal consultation on inspection, good manufacturing practices and risk management guidance in medicines manufacturing
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How to fill out guidance on good data:

01
Start by identifying the purpose of the data - determine why you need the data and what you hope to achieve with it. This clarity will help guide your data collection and analysis processes.
02
Specify the types of data needed - define the specific variables, metrics, or indicators you require to answer your research questions or address your objectives. This will help ensure that you collect relevant and useful data.
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Analyze the data - use appropriate statistical or qualitative analysis techniques to derive meaningful insights and draw conclusions from the data. This may involve performing descriptive statistics, regression analysis, content analysis, or other data analysis methods.
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Interpret and communicate the results - interpret the findings in relation to your research questions or objectives. Communicate the results effectively through reports, visualizations, or presentations that convey key insights and recommendations.

Who needs guidance on good data?

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Organizations and businesses - entities across various industries that use data for strategic planning, performance monitoring, market analysis, or customer insights.
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Government agencies - entities that collect and analyze data to inform policy-making, resource allocation, and program evaluation.
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Students and educators - individuals learning or teaching data-related subjects, who require guidance on best practices for collecting, analyzing, and interpreting data.
In conclusion, anyone involved in data collection, analysis, or decision-making processes can benefit from guidance on good data practices. By following a systematic approach and considering the needs of various stakeholders, one can ensure the quality and reliability of data and derive meaningful insights for informed decision-making.

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