4 answers
Christiana
Student
Charlottesville, Virginia
1
Question
Updated
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Data Analyitcs Minor or Data Science Minor?
Hey! I recently got into the Global Public Health major at my school. I was wondering what the benefits of a minor in Data Science or Data Analytics are, and which one do you think would be more beneficial in order to work with Global health data and policy in the future? (p.s. Im also pre-med!)
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4 answers
Patrick Meyer
Executive - Data Analytics and AI
1021
Answers
Naperville, Illinois
Updated
Patrick’s Answer
Christina, first and foremost, congratulations on your acceptance into Global Public Health. I fully believe that this is a significant achievement that could opens doors to making meaningful impacts in healthcare policy and practice. I think as you dive into this major with either Data Analytics or Data Science, the first thing to do is understand the distinctions between these fields which will help you make an informed decision aligned with your pre-med trajectory and policy interests.
Let's start with Data Analytics, which provides a practical framework for interpreting existing datasets to generate actionable insights that directly inform decision-making processes. This discipline focuses on extracting meaningful patterns from health data to answer specific questions relevant to public health initiatives, policy development, and program evaluation. The skills developed in Data Analytics translate immediately to real-world applications in healthcare settings, making it particularly valuable for professionals focused on implementing evidence-based practices and policies.
However, Data Science encompasses a broader technical scope, incorporating advanced programming, statistical modeling, and machine learning algorithms to build predictive models and uncover complex patterns within large datasets. You should know that with this approach enables professionals to not only analyze current health trends but also forecast future outcomes and develop sophisticated computational solutions to healthcare challenges. The technical depth of Data Science provides powerful tools for research innovation and technological advancement in healthcare analytics.
With all that said, given your pre-med background and interest in health policy, to me Data Analytics is more likely to offer the most direct alignment with your career goals. This path would equip you with immediately applicable skills for analyzing health outcomes, evaluating policy effectiveness, and communicating data-driven recommendations to stakeholders. These capabilities are invaluable for professionals working at the intersection of healthcare delivery and policy implementation, where translating data into actionable insights is essential.
However, if you're drawn to research innovation or developing predictive models for disease outbreaks, population health trends, or healthcare resource allocation, Data Science would provide the advanced technical foundation necessary for these pursuits. You need to know that while this path involves a steeper learning curve with its emphasis on programming and complex statistical methods, it could distinguish your application for specialized medical research programs or technological roles in healthcare.
Both disciplines ultimately require proficiency in data preparation, which means cleaning, organizing, and transforming raw information into structured datasets suitable for analysis. To me this foundational skill ensures the integrity and reliability of your analytical work, regardless of which path you choose. Just know that your decision should reflect not just your immediate academic interests but also your long-term vision for applying these skills in your healthcare career. I truly hope this helps and apologize for being so long winded.
Let's start with Data Analytics, which provides a practical framework for interpreting existing datasets to generate actionable insights that directly inform decision-making processes. This discipline focuses on extracting meaningful patterns from health data to answer specific questions relevant to public health initiatives, policy development, and program evaluation. The skills developed in Data Analytics translate immediately to real-world applications in healthcare settings, making it particularly valuable for professionals focused on implementing evidence-based practices and policies.
However, Data Science encompasses a broader technical scope, incorporating advanced programming, statistical modeling, and machine learning algorithms to build predictive models and uncover complex patterns within large datasets. You should know that with this approach enables professionals to not only analyze current health trends but also forecast future outcomes and develop sophisticated computational solutions to healthcare challenges. The technical depth of Data Science provides powerful tools for research innovation and technological advancement in healthcare analytics.
With all that said, given your pre-med background and interest in health policy, to me Data Analytics is more likely to offer the most direct alignment with your career goals. This path would equip you with immediately applicable skills for analyzing health outcomes, evaluating policy effectiveness, and communicating data-driven recommendations to stakeholders. These capabilities are invaluable for professionals working at the intersection of healthcare delivery and policy implementation, where translating data into actionable insights is essential.
However, if you're drawn to research innovation or developing predictive models for disease outbreaks, population health trends, or healthcare resource allocation, Data Science would provide the advanced technical foundation necessary for these pursuits. You need to know that while this path involves a steeper learning curve with its emphasis on programming and complex statistical methods, it could distinguish your application for specialized medical research programs or technological roles in healthcare.
Both disciplines ultimately require proficiency in data preparation, which means cleaning, organizing, and transforming raw information into structured datasets suitable for analysis. To me this foundational skill ensures the integrity and reliability of your analytical work, regardless of which path you choose. Just know that your decision should reflect not just your immediate academic interests but also your long-term vision for applying these skills in your healthcare career. I truly hope this helps and apologize for being so long winded.
Charlotte Geiger
Public Health Science Student at the University of Maryland
151
Answers
Sykesville, Maryland
Updated
Charlotte’s Answer
Hi!
Congrats on getting into Global Public Health! Both minors are great options, but if you're focused on policy and real-world health trends, Data Analytics is usually more practical and applied—perfect for interpreting global health data and working in public health settings. Data Science is more technical, with coding and modeling, so it’s great if you're interested in research or predictive analytics. Since you're pre-med and interested in policy, Data Analytics might be the better fit, but Data Science could give you an edge if you're into research or tech-heavy work.
Congrats on getting into Global Public Health! Both minors are great options, but if you're focused on policy and real-world health trends, Data Analytics is usually more practical and applied—perfect for interpreting global health data and working in public health settings. Data Science is more technical, with coding and modeling, so it’s great if you're interested in research or predictive analytics. Since you're pre-med and interested in policy, Data Analytics might be the better fit, but Data Science could give you an edge if you're into research or tech-heavy work.
Carlos Tiburcio
Senior Program Manager
15
Answers
Guadalajara
Updated
Carlos’s Answer
Hi Christiana,
Both minors are useful in your field, with Data Analytics being more related to Business Intelligence and creation of Dashboards, graphics, etc to find patterns in data, and Data Science being more related to modeling and predictive analytics and Machine Learning algorithms to forecast behavior.
Be mindful that both disciplines requiere data cleansing and wrangling to be able to have datasets useful for analysis though. In any case, the minor you choose depends on the final end you want to achieve.
Hope this helps!
Both minors are useful in your field, with Data Analytics being more related to Business Intelligence and creation of Dashboards, graphics, etc to find patterns in data, and Data Science being more related to modeling and predictive analytics and Machine Learning algorithms to forecast behavior.
Be mindful that both disciplines requiere data cleansing and wrangling to be able to have datasets useful for analysis though. In any case, the minor you choose depends on the final end you want to achieve.
Hope this helps!
Wellington Cezario 📈📊
Business Analyst
2
Answers
Osasco, SP
Updated
Wellington’s Answer
Hi Christiana,
Data Analytics and Data Science are closely related but serve slightly different purposes. Data Analytics focuses more on interpreting existing data to support decision-making — it's about finding insights and answering specific business questions. Data Science, on the other hand, goes a step further by using programming, statistics, and machine learning to build predictive models and uncover deeper patterns.
If you're choosing between a Data Analytics Minor and a Data Science Minor, it really depends on your goals. Data Science can be a longer and more technical path, often requiring you to learn and apply Data Analytics along the way. In fact, in real-world roles, it's common to wear multiple hats — combining tasks from both fields depending on the needs of the project.
So, if you're aiming for a solid foundation with immediate practical applications, Data Analytics might be the right fit. But if you're interested in a broader and more advanced technical journey, and you're ready for a steeper learning curve, Data Science could open more doors in the long run.
Data Analytics and Data Science are closely related but serve slightly different purposes. Data Analytics focuses more on interpreting existing data to support decision-making — it's about finding insights and answering specific business questions. Data Science, on the other hand, goes a step further by using programming, statistics, and machine learning to build predictive models and uncover deeper patterns.
If you're choosing between a Data Analytics Minor and a Data Science Minor, it really depends on your goals. Data Science can be a longer and more technical path, often requiring you to learn and apply Data Analytics along the way. In fact, in real-world roles, it's common to wear multiple hats — combining tasks from both fields depending on the needs of the project.
So, if you're aiming for a solid foundation with immediate practical applications, Data Analytics might be the right fit. But if you're interested in a broader and more advanced technical journey, and you're ready for a steeper learning curve, Data Science could open more doors in the long run.