Today we will look at the key data analysis stages which ensure that data analysis succeeds. To introduce yourself on what data analysis is, check out our previous blog..https://www.considr.in/?p=5111
- Data preparation
Data preparation involves getting data into a more usable form for analysis. It involves collecting,cleaning and and putting the data into one file or data table primarily for use in analysis.
source: https://www.datawatch.com/what-is-data-preparation/ .
Data should be prepared according to its intended use, usually as informed by the logframe indicators. Thus because qualitative data is numerical,it will need to be prepared for statistical analysis. For the qualitative data,it is important to first identify and summarize the key points. This may involve circling important text, summarizing long descriptions or highlighting critical statements.
2. Data analysis (findings and conclusions)
Data analysis can be descriptive or interpretive. Descriptive analysis involves describing key findings, conditions,states and circumstances uncovered from the data while interpretive analysis helps to provide meaning,explanation or casual relationship from the findings.
Descriptive analysis focuses on what happened, while interpretive analysis seeks to explain why it occurred or what might be the causes.It is important to note that when describing one should focus on the objectives of the findings rather than interpreting it with your own based opinion or conclusion.
3. Data validation
During data validation it is important to determine if and how subsequent analysis will occur. This may be necessary to verify findings, especially with high profile or controversial findings and conclusions. This may involve identifying additional primary or secondary sources to further triangulate analysis or comparisons can be made with other related research studies.
4. Data presentation
Data presentation seeks to effectively present data so that it highlights the key findings and conclusions. It refers to the organisation of data into tables,graphs or sheets,so that logical and statistical conclusions can be derived from the collected measurements
5. Recommendations and action planning
Recommendations and action planning are where data is put to use as evidence or justification for proposed actions. It important to ensure clarity of casualty or rationale for the proposed action,linking evidence to recommendations. One must also ensure that the recommendations are specific,which will help in data reporting and utilization. It is useful to express recommendations as specific action points that uphold the SMART criteria (Specific,Measurable,Achievable,Relevant and Time bound), and that they are targeted to the specific stakeholders who will take them forward.
This marks the end of this step.Next week we venture into the fourth step: Plan for information reporting and utilization. Keep it Considr.