Morris added Alteryx into her Emerging Technologies for Accounting class with assistance from Alteryx SparkED, an education program designed for learners of all skill levels across disciplines, to gain hands-on skills and certification in data analytics. Through SparkED, both educators and students are eligible to receive free Alteryx Designer licenses, as well as access to prescriptive learning paths and teaching resources. The learning paths and resources offer instruction and skill development to help students work towards Core certification.
Although her class targets future accountants, Morris’s projects show that the sky’s the limit for potential use cases.
Ringo Cheng’s team used Alteryx Designer building blocks like Append, Select, Extract, Formula, and Filter to hunt for financial crimes related to the Silk Road, an online black market that operated from 2011 until the FBI shut it down in October of 2013. Despite site owner Ross Ulbricht’s imprisonment, there’s evidence that Ulbricht’s Bitcoin accounts — the currency he used to take commissions — are still active.
“We used Alteryx to scrape the data and analyze whether someone’s still transferring money to and from these accounts,” says Cheng, a senior majoring in accounting and information systems. Bitcoin wallets, as the accounts are known, are anonymous, but every transaction is recorded in the online ledger blockchain.com.
Even though it was just a class exercise, the team’s Alteryx-powered analysis came across some jaw-dropping numbers. “We saw a transfer of around 63,000 Bitcoins to one account,” Cheng says. “Last time I checked one Bitcoin was worth around $50,000. That’s an insane amount of money.”
For Cheng and Such, the appeal of Alteryx is that it combines robust data cleaning and analytics capabilities with a no-code, low-code, drag-and-drop interface that anyone can learn. In effect, it makes data analytics more accessible to more people, no matter what field they’re in.
“We learned to prep, clean, and blend huge amounts of data from different datasets, but in a really simple and transparent way,” Such says. “Basically, I could do all the same tricks with data as a coder without actually being a coder.”
The students said the tool’s visual workflows helped make sense of the data as well.