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Analyzing Your Data

Analyzing your data

After collecting data from all your sources, the next thing to do is to analyze them.

What is Data Analysis?

Data analysis is a process of inspecting, cleansing, transforming, and modeling data to discover useful information, informing conclusions, and supporting decision-making


What are The Processes of Data Analysis?

These processes will help you gather useful data and also help you explore them and discover the pattern(s) in it.

1. Data Requirements

This process relies on the purpose you want to achieve by analyzing the data. Also, it relies on your decisions to pick the type of data analysis you want on what you want to analyze and how to measure it.

2. Data Collection

Based on the requirements you have identified, your data will be collected. There are different sources of data collection as specified in market analysis. The primary and the secondary sources.

3. Data Processing

This process involves organizing collected data for analysis.

4. Data Cleaning

After processing the data, you may discover that the data have errors, or it’s not complete, or it has duplicates. Data cleaning will help you prevent and correct errors.

5. Data Analysis

This process involves exploring the data. As you do so, you start to understand the messages from the data. At this stage, you can either subject the data for more data cleaning or collect more data.

6. Data Interpretation

This is the process of translating the data to either words or tables/charts. This will give a better understanding and help you define your next step.

Data collection has been divided into qualitative data and quantitative dat.

The Quantitative Data Analysis

This type of data is collected by administering close-ended questions i.e asking multiple-choice questions. This type of data is interpreted based on numerals. To analyze this data, first, prepare the data for analysis by following the data analysis processes.

Methods of Quantitative Data Analysis

1. Descriptive Statistics: This method will help you summarize and find patterns in the data. It is based on numbers only. You will want to measure frequency (count, percentage), central tendency (mean, median, mode), variation (range, variance), and position (percentile, ranks).

2. Inferential Statistics: This method is used for making predictions for larger research. It is more complex and it can be used to estimate parameters and for a hypothesis test.

The Qualitative Data Analysis

Rather than numbers, qualitative data is made up of words, images, symbols, and observations. Prepare for data analysis by familiarizing yourself with the data, resisting the objective of the research, developing a framework, and identifying patterns.

Methods of Qualitative Data Analysis

1. Content Analysis: If you want to analyze your interviewees’ responses, you can use this method. This method is used to analyze your documented data. It is the most common method of data analysis.

2. Narrative Analysis: To analyze content from your different data sources. Such as face-to-face interviews, field observation, or surveys.

3. Discourse Analysis: To analyze discussions/interactions with individuals.

4. Grounded Theory: It is used to explain why a particular phenomenon occurred.

Enroll in this course at BizSkills Academy to learn more.

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