Part 6: DATA ANALYSIS TECHNIQUES

Understanding the Tool

Once you have framed your questions and understood your dataset, it’s crucial to familiarize yourself with the tool(s) that you will use for your analysis.

For context, data analysis tools means the software(package) you can use to analyze your data. There are so many of these software but I will mention a few: Excel, PowerBi, Tableau, SQL, STATA, SPSS, R, Python, etc.

For those embarking on their data analysis journey, envision these tools as modes of transport. Just as choosing between walking, driving, or flying depends on the journey, selecting the right tool is imperative for your analysis. For instance, walking (basic tools) may suit some analyses, while flying (advanced tools) is necessary for others.

It’s not sufficient to only learn all the tools but understanding how the tool works, when and why to use them is crucial. Consider this learning path as a journey: start by mastering the basics (learning to crawl) with simple tools before sprinting towards complexity ( learning to run).

Remember, knowledge and experience in one tool can be translated into the learning of another. Stay tuned for my upcoming posts where I delve into each tool’s nuances and sophistication levels

#DataAnalysis