Training for Data Analytics Involves More Than Numbers
Four or five years ago, Hale recalls, he began getting calls from some of his political science alums, all needing help with the same problem.
“Do you know anybody who does stuff with data? Like analyzing it, making pretty pictures, doing deep dives on stuff?” they asked Hale.
So Hale, being a good steward for his students, began incorporating data analytics into his teaching, especially for students pursing Seton Hall’s master’s in public administration degree. He identified enough courses on data mining and data visualization across campus — including in the computer science and mathematics departments — to create a concentration in data analytics in the MPA program. He then put his own twist on the subject by creating a course on the ethical challenges of Big Data.
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There will always be well-paying jobs for the number-crunchers who mine and compile data, Hale says. The ability to do data visualization or governance to organize data in more easily digestible and understandable ways has a secure place in the job market as well, but there is risk associated with strictly following the numbers.
“One of the things computer scientists and mathematicians all tell me is that if you torture it enough, data will confess to anything,” says Hale. “That’s really where the ethics part comes in.”
Hale says that asking the right questions is the foundation of strong data ethics. Questions must be presented in a way that’s careful not to deal in stereotypes or “reinforce existing problems or biases.”
Incorporating Data Analytics into Programs Across Campus
For as much as job growth in data analytics is booming, Hale believes interest in data analysis from employers may be even higher.
“There will be more jobs created for someone who understands data analytics,” says Hale. “There will be a salesperson who understands data, an HR person who understands data, a logistics person who understands data.”
Those employees must be skilled in their fields but also have enough basic understanding of data analytics to communicate with the data scientists who are putting the information together.
“You need to understand what they’re telling you rather than just taking it at face value,” says Hale. “You have to train nontechnical people with enough technical capacity to ask the right questions.”
Adding that technical training can also be part of the answer to higher education’s existential crisis about value, says Hale.
“I personally think that a philosophy degree, where you teach someone how to think, is a wonderful attribute,” he says. “But on top of that, if you can add some basic data analytic skills, that is a combination that I think a lot of colleges and universities are looking into.”
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