Who Needs Data Analysis Skills?
If you are doing research, implementing a new strategy at your company, improving something about yourself or trying to make decisions based on trends, you need data analysis skills. Data analysis is the process of examining data to understand and interpret it, and you don’t need to be highly gifted with technical or statistical skills to be good at it. You just need to be able to make sense of numbers and words or identify patterns. Essentially, analyzing data requires you to “put two and two together” or draw conclusions based on evidence. Take note: I am not saying that data analytics doesn’t require technical and statistical skills; I am saying that data analysis does not. Allow me to explain the difference.
I would describe data analytics as a computational strategy to detect trends and make discoveries. This would typically require a combination of skills in statistics, programming, data visualization AND analysis as the process includes getting data, doing some cleaning, formulating hypotheses, testing those hypotheses, running models and interpreting the results. On the other hand, data analysis is simply the process of examining the data to figure out what it means. It’s part of the analytics process (interpretation of results), but it’s also useful for understanding any complex topic or set of data in general.
If you study Literature, you’ll need analysis skills to be able to interpret texts that you’re reading. If you’re a Consultant, you’ll need analysis skills to be able to create relevant solutions for your clients. If you’re an Accountant, you’ll need analysis skills to identify inconsistencies in expected numbers and determine how to deal with them. I could go on and on, but the bottom line is that everyone can benefit from having data analysis skills and the only tool you need to use is your brain. It’s about examining things in detail in order to connect the dots for whatever your goals are.
If you want to improve your data analysis skills, here is a four-step process that you can follow:
Collect data: Assemble all the information you want to analyze. You could do a simple survey, look at statistics on your social media page, do a series of interviews with people, look at the stats on your smartwatch or health apps, find a dataset online or just get creative!
Make observations: Compile a list of all your discoveries, no matter how simple they are. Here are some examples: “70% of people chose this response on my survey”, “3 people from my interviews said the same thing”, “20% of my followers are from the same country”.
Develop conclusions: After making observations, keep asking yourself, “What does this mean?” It is not enough to only list observations. You need to interpret what you discover, but be careful as you should try not to make too many assumptions.
Determine the way forward: Based on your interpretations and the reason for your analysis, you can formulate an action plan or compile a list of recommendations to determine what you should do next.
In summary, you do not have to work in tech to have data analysis skills. All you need is the ability to interpret data and turn it into valuable information or insights!
