Data Collection & Cleaning
- Data analyst will gather data from various sources, including databases, APIs, and files.
- They will ensure data quality by identifying and rectifying inconsistencies, missing values, and errors.
- Data cleaning which will involve standardizing formats, handling outliers, and ensuring data accuracy.
Interfacing with faculty and staff
Designing and testing databases
Providing oversight on data entry
Data Manipulation and Wrangling:
- The analyst will transform raw data into usable formats. This includes merging datasets, creating new variables, and reshaping data.
- They will use tools like Excel, SQL, Python, and R to manipulate and wrangle data effectively.
Exploratory Data Analysis (EDA):
- EDA will involve exploring data to understand its characteristics, distributions, and relationships.
- The analyst will visualize data using charts, histograms, scatter plots, and summary statistics.
- Identifying trends, patterns, and outliers.
Statistical Analysis and Modeling:
- The analyst will apply statistical techniques under the guidance of PI and research teams.
- They can perform regression analysis, hypothesis testing, clustering, or time series analysis, as recommended by the PI.
- Machine learning models (e.g., predictive models) will also be built to make data-driven decisions.
Domain Knowledge Application:
- The analyst will develop a working understanding of the specific healthcare and dental data domain.
Reporting and Visualization:
- The analyst will create clear and actionable reports, visualizations, or presentations, as requested by the PI.
- Stakeholders (such as PIs, or clinicians) will be able to use these insights to make informed decisions.
- Tools like Tableau, Power BI, or custom scripts will be used to generate visualizations.
Data Governance and Security:
- The analyst will ensure compliance with data privacy regulations (e.g., HIPAA for healthcare data and other DUA specifications).
- They protect sensitive information and maintain data security.