How to Get Started with Data Analytics

This monthly blog highlights and discuss emerging trends and challenges related to healthcare data and its ever changing life cycle.

By Ryan Sandefer, MA, CPHIT, and David Marc, MBS, CHDA


As instructors, one of the most common questions we receive about data analytics is, “How do I get started with data analytics?” We will try to answer by starting with the simple follow up questions below.

Have you ever done one or more of the following?

  • Examined trends within a dataset
  • Produced descriptive summaries about a group
  • Generated a graph to explain a finding or result
  • Developed a report to disseminate information

If you have ever participated in any of these tasks, you’ve already gotten started with data analytics. It is important to always remember that the area of data analytics includes an extremely broad set of skills, and most HIM professionals have already used these skills in some capacity. So, you’ve probably already started with data analytics.

But how do you take it to the next level? One of the growing areas of need related to data analytics involves utilizing various methods of data extraction and competencies for creating statistical summaries. As we all know, healthcare is collecting more and more data, while the requirements for creating information, tracking, and being accountable for healthcare populations is increasing. Health information management professionals are being asked to be more competent with these methods of collecting, analyzing, and presenting data to meet this growing need.

Our teach philosophy is experiential learning focused on solving real-world problems improves understanding. An effective method for getting more involved with data analytics is to learn with step-by-step methods for extracting data from a database (including querying scripts), cleansing and prepping data for analysis, and conducting statistical analysis to answer questions. This hands-on approach provides HIM professionals with essentials skill for exploring data using real-world tools while also conducting research. We have recently written a book based upon this teaching philosophy.

If you’re interested in data analytics, our recommendation is to find everyday opportunities to analyze data. No project or dataset is too small. Start with completing a data analytics project for work, school, or home, and then continuously develop more skills to create and present information that improves the understanding of the world around you. Happy analyzing!

Author Info

Ryan Sandefer

Assistant Professor and Chair

Department of Health Informatics and Information Management

College of St. Scholastica


David Marc

Assistant Professor and Graduate Program Director

Department of Health Informatics and Information Management

College of St. Scholastica

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