4 answers
Prerak
Student
Stafford, Texas
1
Question
Asked
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What are some real world applications of Data Science?
I am a high school senior planning to pursue data Science in college. I have always been interested in computer science and math, and data Science seems like an exciting field that combines both. I want to learn more about this major to ensure it's the right choice for me.
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4 answers
Sneha Deb
Tech Consultant
167
Answers
Edison, New Jersey
Updated
Sneha’s Answer
Hi Prerak! Data Science is a perfect blend of math, coding, and real-world problem-solving! In the real world, data science powers things like predicting stock trends, improving healthcare diagnoses, creating recommendation systems (like Netflix and Spotify), optimizing delivery routes (like Amazon), and even detecting fraud in banking. It’s used in sports analytics, climate modeling, marketing, and more. If you love math and computer science, data science can open doors to many industries while keeping your work both creative and analytical. This path has tons of opportunity so look into what interests you and find experiences to match! Good luck!
Carlos Tiburcio
Senior Program Manager
10
Answers
Guadalajara
Updated
Carlos’s Answer
Hey Prerak! As a certified Data Scientist myself, I can tell you that Data Science is an exciting field that provide analysis and actionable insights for the businesses to act based on data. Your interest in computer science and math will help you a lot as Data Science implies statistical analysis, so understanding of probability distributions, statistical hypothesis testing and related subjects is very important. Also, Python is by far the software language of choice for developing machine learning models and analyze data, although there are other good languages like R that can do the job, Python is definitely ahead in terms of packages and support.
Many fields and industries that rely in data like Finance, Healthcare sciences, Software industry, Government areas like car traffic management or urbanism, etc benefit from the insights of Data Science.
With that said, I would advise for you to also enter into the realm of Generative AI and learn its uses related to data analysis, as now GenAI can provide analysis and graphs in a very fast way, as well as writing the Python code needed to generate these data analyses. Also, learning to do Data Analysis /Science in cloud environment as AWS, Google Cloud or Microsoft Azure is important as many companies nowadays relies on cloud computing to make their data models, train them and run them for production.
As final advice, you can find many online courses related to Data Science in Coursera.org, Udemy or edX. Coursera courses can be taken at no cost (what they call "Auditing" courses) and there's also very good lessons in YouTube from Harvard Online for free.
In conclusion, everything related with Data Science, Machine Learning and AI has a bright future!
Hope this helps!
Many fields and industries that rely in data like Finance, Healthcare sciences, Software industry, Government areas like car traffic management or urbanism, etc benefit from the insights of Data Science.
With that said, I would advise for you to also enter into the realm of Generative AI and learn its uses related to data analysis, as now GenAI can provide analysis and graphs in a very fast way, as well as writing the Python code needed to generate these data analyses. Also, learning to do Data Analysis /Science in cloud environment as AWS, Google Cloud or Microsoft Azure is important as many companies nowadays relies on cloud computing to make their data models, train them and run them for production.
As final advice, you can find many online courses related to Data Science in Coursera.org, Udemy or edX. Coursera courses can be taken at no cost (what they call "Auditing" courses) and there's also very good lessons in YouTube from Harvard Online for free.
In conclusion, everything related with Data Science, Machine Learning and AI has a bright future!
Hope this helps!
Diana Cobian
Sales
16
Answers
Guadalajara
Updated
Diana’s Answer
Hey Prerak! It's awesome that you're thinking about diving into data science! It's a lively and expanding field that mixes math, stats, and computer science to dig out insights from data. Check out some cool ways data science is used in different areas:
1. Healthcare & Medicine
- Disease Prediction & Diagnosis: AI looks at medical records and scans to spot diseases like cancer early on.
- Personalized Medicine: Data helps doctors tailor treatments to fit a patient’s genes.
- Pandemic Tracking: Data science helps track and predict how diseases like COVID-19 spread.
2. Business & Finance
- Fraud Detection: Banks use machine learning to catch fake transactions instantly.
- Stock Market Prediction: Analysts create algorithms to guess stock prices and trends.
- Customer Insights: Companies like Amazon and Netflix suggest products and shows based on what users like.
3. Tech & Artificial Intelligence
- Chatbots & Virtual Assistants: Tools like Siri and Alexa use data science to understand what we say.
- Autonomous Vehicles: Self-driving cars use data to make smart driving choices.
- Image & Speech Recognition: Apps like Google Photos use data science to recognize objects and turn speech into text.
4. Sports & Entertainment
- Sports Analytics: Teams use data to boost player performance and plan strategies (like Moneyball in baseball).
- Streaming Recommendations: Spotify and YouTube suggest music and videos based on what you enjoy.
5. Environmental Science & Sustainability
- Climate Change Analysis: Data scientists study weather to predict climate change effects.
- Renewable Energy Optimization: Companies use data to make solar and wind energy more efficient.
6. Government & Policy Making
- Crime Prediction & Prevention: Police use data to find crime hotspots and manage resources better.
- Smart Cities: Data helps plan cities to improve traffic, cut pollution, and enhance infrastructure.
Why Data Science is a Great Choice
If you love math and computer science, data science is a great mix of both. It opens up exciting career paths in nearly every industry, from big tech companies like Google to healthcare, finance, and even sports analytics.
1. Healthcare & Medicine
- Disease Prediction & Diagnosis: AI looks at medical records and scans to spot diseases like cancer early on.
- Personalized Medicine: Data helps doctors tailor treatments to fit a patient’s genes.
- Pandemic Tracking: Data science helps track and predict how diseases like COVID-19 spread.
2. Business & Finance
- Fraud Detection: Banks use machine learning to catch fake transactions instantly.
- Stock Market Prediction: Analysts create algorithms to guess stock prices and trends.
- Customer Insights: Companies like Amazon and Netflix suggest products and shows based on what users like.
3. Tech & Artificial Intelligence
- Chatbots & Virtual Assistants: Tools like Siri and Alexa use data science to understand what we say.
- Autonomous Vehicles: Self-driving cars use data to make smart driving choices.
- Image & Speech Recognition: Apps like Google Photos use data science to recognize objects and turn speech into text.
4. Sports & Entertainment
- Sports Analytics: Teams use data to boost player performance and plan strategies (like Moneyball in baseball).
- Streaming Recommendations: Spotify and YouTube suggest music and videos based on what you enjoy.
5. Environmental Science & Sustainability
- Climate Change Analysis: Data scientists study weather to predict climate change effects.
- Renewable Energy Optimization: Companies use data to make solar and wind energy more efficient.
6. Government & Policy Making
- Crime Prediction & Prevention: Police use data to find crime hotspots and manage resources better.
- Smart Cities: Data helps plan cities to improve traffic, cut pollution, and enhance infrastructure.
Why Data Science is a Great Choice
If you love math and computer science, data science is a great mix of both. It opens up exciting career paths in nearly every industry, from big tech companies like Google to healthcare, finance, and even sports analytics.
Jesse Petre
Data Analyst
2
Answers
Columbus, Ohio
Updated
Jesse’s Answer
Hey Prerak, I'm a data analyst, which is a less-complex field than data science. You asked for practical examples, so I'll share a little about what I do. In my day-to-day job I am writing SQL queries to look for anomalies and trends in the data. I work in billing at Verizon, so I am looking for things like "show me all the customers that got billed for a product that shouldn't exist" or "show me the list of customers that had their bill increase by more than 1,000% from the previous month." I'm also scanning the database to ensure all bills were produced with the required regulatory language on it. I also extract billing data and feed into a trending system to keep track of, for example, how much do we bill all our government customers every month, and is this trending up or down? If we notice an unexpected trend, I can pass it off to an analyst to research further and determine why.
Data science takes this one step further and introduce predictive analytics. A great example would be, "we want to introduce a new cell phone plan priced at $40/mo only for customers that already have our fiber tv service. If we roll this out, how many customers will sign up, and what are their demographics?" Or perhaps more generally: "We want to roll out a new premium feature on our phone plans, how much should we charge for it to maximize the return on investment?" Data science uses advanced models to predict these questions and answer them as accurately as possible.
Data science is a very HOT field right now, but requires extensive mathematics and statistics knowledge. The most sought-after roles are even requiring PhD degrees, but the pay is fantastic.
Hope that helps!
Data science takes this one step further and introduce predictive analytics. A great example would be, "we want to introduce a new cell phone plan priced at $40/mo only for customers that already have our fiber tv service. If we roll this out, how many customers will sign up, and what are their demographics?" Or perhaps more generally: "We want to roll out a new premium feature on our phone plans, how much should we charge for it to maximize the return on investment?" Data science uses advanced models to predict these questions and answer them as accurately as possible.
Data science is a very HOT field right now, but requires extensive mathematics and statistics knowledge. The most sought-after roles are even requiring PhD degrees, but the pay is fantastic.
Hope that helps!