Does your data talk back?Mar 15, 2023
When working with data, especially if you're not very familiar with it, it's important to ask questions to make sure you're representing the data accurately and honestly as you analyze and visualize it. Here's my list of recommended questions:
What am I trying to measure?
Let this guide your decisions for selecting a data set, completing your analysis, and creating visualizations.
How was the data collected?
How data is collected has an impact on what is measured and counted, so it's important to investigate how your data was collected, who was counted, and how variables were created.
Who collected the data?
Who collected the data can impact the quality of the data and what was included and excluded. It's important to understand the source and details behind a data set.
Is this the right data to answer the question?
Sometimes it might be the only data available, but it's important to think critically about the data and what questions can actually be answered with it.
What does each variable mean?
It's important to understand the units of each variable and what it actually measures or tells you.
Are some records missing values? Are certain groups or categories excluded from the data? Who is missing from the data collection process?
Sometimes we can impute values for missing records or we can find another data set that fills in the gaps. Other times the data is not available (or shouldn't be imputed). It's important to evaluate who and what is missing from the data.
Is the data formatted properly for analysis?
You may need to reformat the data by pivoting it, adding a new column, or creating new variables before you can analyze or visualize it.
Who’s the audience? What do they need to know?
Let the answers to these questions drive your analysis and visualization design and output. If you need help figuring out your audience and what they're looking for, check out my free Data Viz Design Process workbook and training.
This post originally appeared in my newsletter, the Studio Scoop. Want more stories and data viz tips like this? Subscribe below.
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