Qualitative Data Analysis In 2020

When you’re presented with data, what comes to you first? You try to figure out what it means, right? When data is presented, we all try to find the relationships between them, patterns, and connections that might make sense. Qualitative data is not numerical and is instead collected by interviews, observations, and other similar methods. Once collected, we try to conclude by analyzing the data we’ve gotten. This is what qualitative data analysis is, drawing insight from data collected.

What is Qualitative Data Analysis?

For instance, a clothing company looking to discover recent fashion styles amongst ladies will approach ladies and get answers relating to the research goal. Data collected will then be analyzed by the company, to find recurring patterns. That’s what data analysis entails —examining qualitative data to get significant results.

Qualitative data analysis assists in finding occurrences in traits and characteristics. As qualitative data is all about how people perceive things and their feelings, it helps researchers better understand their customers and effectively deal with any problem.

How to Conduct Qualitative Data Analysis in 2020

Bringing qualitative data together can be quite time-consuming and expensive, so you don’t want it to waste. That’s why getting the analysis right is vital, so you’re not still lost on the right step to take after all the hard work. There are no strict patterns for quality data analysis, but this process will surely get you the results you need.

• Assemble Data Acquired

Data collected sometimes doesn’t make sense when you look at it; it lacks structure and is usually and unarranged. That’s why you must arrange the data collected before analyzing it. A systematic approach is needed in arranging this data; this means you have to translate the data gathered into text by either entering it into a spreadsheet or typing it. 

• Authenticate Data Acquired

To get the right results at the end of the analysis, you need to confirm that the data is genuine. This is a fundamental stage of qualitative data analysis. Your data needs to be consistent and unbiased, and this particular step needs to be repeated until the analysis is over. To confirm data collected, make sure the right processes were followed and that interviews were truly carried out. Make sure all questions were duly answered and that screening was done correctly according to criteria stated.

• Organize the Data Acquired

After weeding out the data that is not valid, there will still be substantial data that requires orderly organization. Go through the research goals and assemble data gotten according to the questions asked; it can be tempting to just work with data as it is, but don’t fall, as it can lead to inconclusive data analysis.

• Revise Acquired Data

There must be errors attached to the data as respondents may accidentally fill some fields incorrectly. This is why it is crucial to check for errors and carefully edit the data to ensure that no error is left behind. This will ensure that results obtained after analysis are accurate and not hampered.

• Create a System 

This is another important aspect of qualitative data analysis; it is the best method to truncate the large data collected. Categorize the data collected into a certain pertain; it will help you develop theories much more easily from your findings. You can categorize based on age or by gender; this will make analysis easier when you can easily focus on age grades or gender. It is one of the top methods to draw knowledgeable conclusions based on patterns derived.

• Rounding Up Analysis

Concluding is an integral part of the analysis process; this is where you systematically present the derived results. Your analysis report should be ready for use at any time; this report needs to present the method used in the analysis and the limitations of your research. The positives and negatives of your research should also be provided in the report. Ensure you also make suggestions based on results and mention areas that could be researched in the future.