1. Data Collection: This involves gathering information from various sources such as surveys, medical records, and laboratory reports. The data must be collected systematically and ethically. 2. Data Storage: Once collected, data needs to be stored securely in databases or data warehouses. This ensures data integrity and availability for future analysis. 3. Data Cleaning: This step involves checking for and correcting errors or inconsistencies in the data. Clean data is essential for accurate analysis. 4. Data Coding: Assigning codes to data items (e.g., using ICD-10 for diseases) facilitates easier analysis and comparison. 5. Data Analysis: Applying statistical methods to interpret the data and draw meaningful conclusions. This may involve the use of software such as R or Python. 6. Data Dissemination: Sharing the findings with stakeholders through reports, publications, or public health advisories.
