3 Important Questions to Glean Insight From Data

Never take anything at face value. We know that Sherlock Holmes was known for solving mysteries using his keen sense of observation and ability to ask the right questions.

Much like becoming a successful sleuth, developing data fluency means learning how to ask some simple questions from the information in front of you. Training your eyes to see the patterns and anomalies as well as asking these critical questions will help you use the clues to get the most out of a data product.

With the components of data and structure under your belt, we are ready to ask the important questions. Let’s see which insights can be revealed from your college search data (from last week’s post) by digging a little deeper.  

1. Where does the data product come from? Knowing the origin of data is just as important as seeing data. Understanding where data comes from means knowing how data was collected and how it was processed before you received it.  It also means considering what the goals and biases of the author of the data product. Following our college search example, we know the national college board develops the rankings, thus providing a neutral perspective.  

During the data origin process, it is also important for you to figure out what the scope of the data is. If the universities in the top 10 studies are only from the Northeast -- then you know that you may want to collect some more information from other geographic regions to compare. Sometimes hidden gems of information lie in the individual relationships or the outliers. Meaning if you are only seeing the averages, you may miss a significant fact in the information specific to your search. Perhaps, Northwestern University was further down the rankings due to a specific dimension classification in the data. Being able to go back and question outliers may reveal their admission rate was 1% but in all other categories the school would be a best match for you.

2. What can you learn from it? Your ah-ha moment! This is when you move from comprehension of what is it to what it means. Data visualization helps you see data results easily and determine if they compare to your expectations - thus encouraging you to do more of the same. Or alter your course, if results were unexpected, and take new action. So you were able to filter down your search results to 15 schools that best match the criteria you are looking for - tuition, retention rate, class size and academic discipline emphasis.

A skilled data author will create data products that emphasize the message to be conveyed. Many different tables, charts and graphs exist and it is an art to be able to choose the most effective visualization. Whether you are looking at a pie chart, bar graph or dashboard, always begin your analysis of each data product with a focal point of a small area. You can build from there. By breaking down complex data into its smallest pieces and finding something comprehensible, you can start to understand both what the author is trying to show and how to read the content.

3. What can you do with it? Now that your eye for discerning data is more discriminate, you can tackle the last question: what now? You are ready for action. The data draws a direct and obvious line between the implications of data and specific actions and decision making. Now you and your child are making your own top 10 list of schools, prioritizing the universities and then applying. This will save you money in the long run and ensure you made the best decision concerning higher education for your child.

Best Practices to Strengthen Your Data Language Foundation

  • Keep an eye out for unexpected distributions, patterns or relationships, and unexpected trends. Like in our example, when Duke wins the NCAA basketball championship, students seeking admission always increase and influence ranking results.

  • Look at comparisons to give context. Reviewing performance results from one year to another provides a historic perspective for further investigation. 

  • Find a starting point and filter down based on findings at the individual level. For example, if it is most important for your child to go to a college in the top rankings and close to home. Start there and build your list.

  • Find actions you can take and do something about. Apply to those universities that are the best fit! 

Just remember, knowledge is having the right answer. Intelligence is asking the right questions!

 

Excerpted with permission from the publisher, Wiley, from Data Fluency: Empowering Your Organization with Effective Data Communication by Zach Gemignani, Chris Gemignani, Richard Galentino, Patrick Schuermann.  Copyright © 2014.