What is the difference between data science and data analytics ?

Answer 1

Todays most common topic......://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article

Answer 2

DA got 50K in the old days, now they call themself DS got paid for 160k for doing the same thing.

Answer 3

Data Analytics:
Scope:
A focused field within data science, often dealing with answering specific business questions.
Focus:
Analyzing existing data to identify trends, patterns, and insights to support business decisions.
Objectives:
To provide actionable insights, optimize processes, and improve decision-making.
Tools and Techniques:
Data querying, data cleaning, data visualization, and statistical analysis.
Example:
Analyzing sales data to identify top-performing products and areas for improvement.

Data Science:
Scope: A broader field encompassing data analytics, data engineering, and machine learning.
Focus: Extracting insights from large datasets, building predictive models, and developing new algorithms.
Objectives: To find patterns, predict future trends, and discover new ways to use data.
Tools and Techniques: Advanced statistical modeling, machine learning, and predictive analytics.
Example: Developing a machine learning model to predict customer churn.

In essence, data science is about using data to create new knowledge and capabilities, while data analytics is about using data to understand the present and make informed decisions. Data scientists often work with more complex, unstructured data and build predictive models, while data analysts typically work with structured data and focus on answering specific questions.