Data Science or Data Analytics?

@c0dewithharry

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Why it worked

The video addresses a common point of confusion for individuals looking to enter the tech field, specifically differentiating between two popular and related career paths. By clearly outlining the differences in roles, responsibilities, and required skills, it provides valuable information that helps viewers make informed decisions about their career choices. The use of visual aids and a direct comparison format makes the content easily digestible and engaging.

Summary

This video compares Data Science and Data Analytics as career paths, explaining the roles, responsibilities, and required skills for each. It highlights that Data Analytics is more focused on understanding past data and decision support, making it an easier entry point into tech. Data Science, conversely, involves more complex mathematical and coding skills for predicting future outcomes, presenting a higher barrier to entry but also offering greater growth potential and higher salaries.

Structure

1Introduction to Data Science vs. Data Analytics
2Defining Data Analytics and its tasks
3Defining Data Science and its tasks
4Comparing job opportunities and entry barriers
5Concluding thoughts on career choice

On-screen text

Data Scientist Data Analyst Best career option 2026 Career Trends Data Analyst Data Scientist What is Data Analytics? Understanding existing data What happened? Why did it happen? How did it happen? A Data Analyst's daily work includes: - Writing SQL queries - Understanding data and explaining it to business teams - Creating dashboards using Excel, Power BI, or Tableau - Delivering reports and insights to support better decision making. What is Data Science? AI driven systems so that day to day work becomes easier - Linear regression - Logistic regression - Random forest - Deep learning Job Opportunities? Data Analyst Data Scientist It makes your transition into tech easier. Data Scientist It has a slightly higher barrier to entry. MATHEMATICS CODING DEEP TECH KNOWLEDGE

Original caption

Which Pays More: Data Science or Data Analytics? | Data Science vs Data Analytics #codewithharry #webdeveloper #dataanalytics #datascience #datascientist

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Transcript

Data Science or Data Analytics? If you are confused about this topic, then today's video is for you. I won't waste your time, I'll get straight to the point and tell you which one can be the best career option for you. Looking at the career trends of 2026, Data Scientist and Data Analyst are both very lucrative job roles. Many people get confused whether Data Science and Data Analytics are the same things, when clearly they are not. So let's find out about both careers. First, let's talk about what is Data Analytics? The main focus of Data Analytics is to understand existing data and to understand what happened? Why did it happen? How did it happen? And what decisions should the business take going forward? A Data Analyst works closely with business teams and management. A Data Analyst's daily work includes: - Writing SQL queries - Understanding data and explaining it to business teams - Creating dashboards using Excel, Power BI, or Tableau - Delivering reports and insights to support better decision making. On the other hand, what is Data Science? Data Science is a bit more towards prediction. Let me explain. In this too, data is understood, but predicting the future is a much bigger goal. This involves deep mathematical and technical knowledge. In this, we use statistical tools and machine learning models to understand big data sets so that the future can be predicted. Tools like linear regression, logistic regression, random forest, deep learning are used. A Data Scientist writes a lot of code compared to a Data Analyst. They use mathematics and coding to build predictive models. Now let's talk about job opportunities. If I talk about Data Analyst roles, it's a role that makes your transition into tech easier. It's an easy entry point for people who have never coded in their life or have never worked with computers much. You can start learning Data Analysis quite easily. On the other hand, Data Scientist jobs have a slightly higher barrier to entry. It means you need to learn coding, mathematics, and deep technical knowledge. These things take time and effort. But at the same time, Data Analyst has an unfair advantage. I hope you understood which one is for you. Which role is better for you?