Mohammed Al hadhri- MEAL Sr. Coordinator 

One of the most important phases in the monitoring and evaluation field is data analysis in which the transformation of unprocessed data into usable information. Researchers are being able to understand information and findings as a result of data analysis. It entails the act of comprehending, synthesizing, and arranging the data in a way that responds to the goals and indications of any designed project. 

The M&E role handling the project requires a well-thought-out plan for data analysis before the initiation of the study. This plan should include an outline of the time frame and characteristics of data, methods and data structure required by the statistical tools and templates to achieve stated objectives and carrying out the analysis and interpretation of the results of the studies such as needs assessment, baseline/endline, market assessment and end-evaluation studies.

A crucial component of data analysis is the data collection process. It is the process of compiling information from diverse sources to assess a program's or project's effectiveness. Both qualitative and quantitative data can be collected. Therefore, the following techniques are used to gather qualitative data: focus groups, surveys, interviews, and observation. On the other hand, methods for gathering quantitative data include questionnaires, surveys, and secondary data. This entails summarizing the relevant indicators and tabulating data to establish relationships. Subsequently, a comparative analysis of important indicators among respondents from different target groups, geographical areas, etc., will be conducted to offer more precise insights into the realities in the fields. In addition to these procedures, sophisticated tests like the correlation coefficient, T-test, variance test (ANOVA), simple regression analysis, and multiple regression analysis for determining a cause-and-effect relationship.

As M&E employees under the influence of technological advancements in data analytics, data analysis plays a huge role in decision-making, providing a better, faster and more efficacious system that minimizes risks and reduces human biases. Moreover, four types of data analysis techniques are usually used when dealing with data received from the intervention filed as follow:

1.      Descriptive Analysis: This is the most fundamental and common sort of analysis. It is the simplest to accomplish from a technological standpoint. There are several descriptive statistics that provide us with methods for summarizing a set of data. (For example, counts, minimum and maximum values, sums, ratios, proportions and percentages, mean/median/mode, and dispersion measures (standard deviation and range)).

2.      Diagnostic Analysis: This form of analysis looks for patterns beneath the surface, attempting to answer the question “why is this happening?”

3.      Predictive Analysis: This entails making predictions about future outcomes based on historical data.

4.      Prescriptive Analysis: This narrows our focus on the many courses of action we could follow and the possible results. The goal of prescriptive analysis is to provide a solution to the question, “What should we do?”

One another crucial thing is how to present your findings whether they are qualitative or quantitative. Data Visualization is the process of putting your data into charts and graphs which provide information about what the data is showing. However, you may want to use a specific software to serve your purpose, especially where the ‘look and feel’ of the final presentation or Dashboard is important or where you’re circulating documents for high-impact advocacy or the promotion of your learning and ideas. Moreover, Excel, Power BI, and Tableau are the most visualization tools used in the process of presenting data. Also, you could discover that you require more than just basic Excel graphs when your data gets a little more complicated. You could want to start looking into pivot charts for this, since they allow for rapid and simple analysis of cleaned data. The slicers can be used to assist in the creation of straightforward interactive dashboards for in-person presentations.

To conclude, data analysis is essential in the data-driven world of today. It assists businesses in utilizing data to make decisions, monitor processes, and evaluate projects. By transforming row data into valuable insights in which data analysis enables organizations to recognize opportunities, reduce risks, and improve overall performance.

1.  https://devinsights.co.in/data-analysis-as-a-salient-step-in-the-process-of-monitoring-and-evaluation/#:~:text=Data%20analysis%20is%20important%20to,it%20is%20not%20achieving%20it.
2. https://humanitarianglobal.com/the-5-forms-of-data-analysis-in-me/