5 Skills You Need to Succeed in the Health Data Industry

As healthcare becomes more reliant on data, expectations for professionals in analytics roles are changing. It is no longer just about pulling reports or working in spreadsheets. Today’s health data professionals are expected to interpret complex information, communicate insights clearly, and adapt to evolving technologies.

For those considering a move into health informatics or looking to grow in their current role, understanding which skills matter most can help guide that next step. While technical expertise remains important, many of the field’s differentiators go beyond tools and programming languages.

Insights from Sanket Shah, who teaches in UIC’s Online Master of Science in Health Informatics program, offer a clearer picture of what it takes to succeed in this field today. Based on his experience in healthcare analytics, success comes from a mix of technical skills, communication, and continuous learning.

1. Strong Foundations in Data and Querying

A strong foundation in how data is structured, stored, and accessed is essential for any role in health data analytics. This often begins with database concepts and querying languages. As Shah explains, “getting a good handle on database technology and querying language is a foundational piece.”

That foundation becomes even more important in healthcare, where analysts are often working across clinical, financial, and claims data. Connecting those sources allows analysts to move beyond surface-level reporting. He also notes that understanding how data connects is what really builds capability. Even as tools change, that underlying knowledge stays relevant and supports everything else analysts do.

2. Familiarity with Programming and Analytical Tools

Beyond querying data, many analysts expand into programming and the use of analytical tools. Languages like Python are commonly used to manipulate data and support more advanced analysis. Shah describes this as a natural progression, saying you “migrate into more advanced programming languages, whether that be Python or other technologies like that,” and that it is “becoming more and more important.”

At the same time, he emphasizes that it is not about mastering every tool. Instead, understanding how these tools work and how they support data workflows is what matters most. In practice, analysts often work across multiple platforms. The ability to adapt and learn new tools is just as important as any single technical skill.

3. AI Literacy and Emerging Technology Awareness

AI is becoming a more visible part of healthcare analytics, and analysts are expected to understand how to use these tools effectively. Shah points to a clear shift in the field, noting that “understanding how to use GPT tools and technologies like Claude or Codex is where I am seeing a shift.”

These tools can help accelerate analysis and uncover insights more quickly, but they are not a replacement for the analyst. They are meant to support the work. He also emphasizes that these technologies should be used thoughtfully. Analysts still need to validate outputs and ensure the insights make sense in a real-world context.

4. Communication and Data Storytelling

Technical skills are only part of the role. Analysts also need to communicate what the data means in a way others can understand. As Shah explains, “you have all this great data, but you are also responsible for displaying it visually or describing it through verbal communication.” He emphasizes that getting to the meaning behind the data is critical. “What does it all mean? The ‘so what’ is super important.”

This becomes especially important when presenting to leadership or contributing to strategic decisions. Health data analysts are expected to clearly explain insights, provide context, and connect data to outcomes. Strong communication skills enable analysts to move from simply reporting data to influencing decisions.

5. Curiosity and a Continuous Learning Mindset

Curiosity is one of the most important traits for success in this field. Analysts need to ask questions, explore new approaches, and stay engaged with how the industry is changing. Shah describes it simply as “the ability to be curious.” He encourages professionals to “ask questions” and think about “why we are doing things this way.”

He also highlights the importance of learning from others. “Network with your classmates, your professors, your colleagues, and understand what they are doing.” Staying current is just as important. Following industry trends and reading trade publications helps analysts stay informed and adaptable as new tools and approaches emerge.

How These Skills Are Built in Practice

Building these skills requires more than theoretical knowledge. It comes from applying them in real-world situations. In Shah’s course, BHIS 540: Essentials in Health Data Science, students start by working directly with data and learning to bring together different sources. As he explains, “we really build week after week on those skills,” starting with hands-on data work and learning how to create outputs.

From there, the course moves into applied case studies. “We have created a case study where a fictitious CIO has asked you to build a business intelligence plan,” which requires research, analysis, and making recommendations. At the end, everything comes together in a final project. “It all accumulates at the end with a prototype,” where students apply what they have learned to build a solution.

The goal is to help students become comfortable both working with data and communicating insights, which reflects how these skills are used in real healthcare environments. Programs like the Online Master of Science in Health Informatics (MSHI) at UIC are designed with this type of applied learning in mind, helping professionals prepare for the evolving demands of the field.