WIL Technical and Transferable Skills

Context

During my internship at Gold Coast Health under the Robina Health Precinct, I worked as a data analyst intern for the IMPACCT team. The focus of my work was to analyze and process data to assess whether community services—especially complex discharge services—were improving patient outcomes by reducing hospitalizations and emergency department visits. Throughout this internship, I had the opportunity to apply a combination of technical skills in data analysis and transferable skills, such as communication and problem-solving. The internship was especially rewarding because it connected my Master of IT in Data Analytics studies with my pharmacy background, giving me insights into both data and healthcare practices.

Action

During this internship, I developed and applied several key technical skills:

1. Excel for Data Management and Communication
   I worked with six large Excel spreadsheets, each containing over 100 columns and approximately 205,000 rows. I used Excel for preliminary data exploration, as it allowed me to understand the structure of the data before processing it further. Since the multidisciplinary team was familiar with Excel, I also relied on it to communicate insights and ask for clarifications about data columns.
2. KNIME for Data Cleaning and Integration
   To handle large datasets efficiently, I used KNIME, which offers a node-based workflow for fast and scalable data processing. I performed data filtering to extract only the necessary columns and integrated multiple datasets, such as community service appointments and emergency department admissions, to create a unified view of patient data. I also removed irrelevant rows and noise from the data, which was crucial to ensure the accuracy of my analysis.
3. Power BI for Data Visualization and Reporting
   After cleaning and normalizing the data in KNIME, I used Power BI to create interactive dashboards, including pie charts, line graphs, and tables. I implemented slicers to filter information efficiently and built patient journey visualizations to help my manager gain new insights. Using Power BI allowed me to present data in an engaging way that was easy for non-technical professionals to understand, providing a new perspective on their services.
4. Reporting and Documentation
   I compiled the insights from my analysis into a comprehensive written report using Word. The report included data sources, key findings, challenges, and recommendations. This experience helped me improve my documentation skills by writing in a clear, structured, and professional manner, ensuring that the report was understandable for all stakeholders.

Result

The technical skills I developed during this internship were closely tied to my university studies, which provided a strong foundation. For example, data processing courses at university made me proficient with tools such as Excel, and Power BI, allowing me to start the internship smoothly. However, I still faced a learning curve at the beginning—I wasn’t initially fast in applying the tools, but through continuous practice, I became more efficient and effective over time.

My university studies in SQL (Structured Query Language) and MySQL Database System were also invaluable. When the data analyst provided me with data extracted from the MySQL database, I requested the SQL queries he used to extract the information. My understanding of SQL structure helped me comprehend the data organization and logic behind the datasets, which made it easier to integrate and analyze the data.

One of the key challenges I faced was the lack of uniform diagnostic coding within the datasets. Without a consistent coding system, it was difficult to compare patient groups and draw definitive conclusions about the services’ impact. To overcome this, I focused on analyzing trends among the patients who received services, but the complexity of patient journeys still made it hard to demonstrate clear outcomes.

Learning

This internship enhanced both my technical and transferable skills. I became more proficient in data cleaning, integration, and visualization, applying Excel, KNIME, and Power BI more efficiently than before. I also improved my communication and problem-solving skills by interacting with a multidisciplinary team, learning to ask the right questions and align my work with their needs.

Additionally, I recognized the importance of domain-specific knowledge in healthcare data analytics. Moving forward, I plan to further my understanding of diagnostic coding systems, such as Australian DRG codes, to perform more meaningful analyses in the healthcare field.

To improve my skills in Knime and Power BI, I watched tutorials online and explored advanced functions, which allowed me to structure my reports in an organized way. This self-directed learning helped me apply theoretical knowledge to practical scenarios, demonstrating the importance of continuous learning in my field.

Through this experience, I also learned to navigate the constraints of government IT systems, such as limited software access. This insight will be beneficial as I pursue future roles in public healthcare organizations, where understanding system limitations and data privacy protocols is crucial.