Of the $2 trillion spent on healthcare in the United States annually, an estimated $60 billion is lost to healthcare fraud. This results in higher premiums and out-of-pocket expenses for patients, as well as increased insurance costs for employers. Even worse is the growing human toll: over six million Americans are addicted to prescription drugs, which account for over 40% of drug overdose deaths. In 2016, health care providers wrote over 214 million opioid prescriptions. For data scientists and healthcare data analysts tasked with researching fraud, waste, and abuse in healthcare, the challenge is data scale. Researchers armed with spreadsheets or traditional tools used for healthcare data analytics are unable to analyze the billions of prescription records, healthcare claims, or alternative data sources that could help identify issues and learn how to prevent fraud and abuse in healthcare.