Data Science vs Data Analytics: Key Differences Explained 📊

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In this video on “Data Science vs Data Analytics," we will look into the key differences between Data Science and Data Analytics. Data Science is the process that includes acquiring data, cleaning data, exploring data, and building models. Data Analytics is the process of using these models to draw conclusions and make predictions.

✅ Which is better, data science or data analytics?
Choosing between a career in data science and data analysis ultimately depends on your interests and strengths. If you are inclined towards more technical, algorithmic challenges and enjoy delving deep into machine learning and predictive modeling, data science might be the right path.

✅Does data science pay more than data analytics?
Both data analytics and data science have lots of room for growth when it comes to salary and responsibilities. The average annual salary for a Data Analyst is $64,000 and the average annual salary for a Data Scientist is $127,000. As you can see, the average salary for a Data Scientist is higher.

✅Does a data analyst require coding?
Data analysts need to be able to work with large datasets, use statistical methods to analyze the data, and apply mathematical models to interpret the results. They may also need programming languages like Python and R to write and run statistical models and algorithms.