Digference between data science and data analytics

Question

Accepted Answer

Data science focuses on extracting insights and building models from data, while data analytics focuses on analyzing and interpreting data to make informed decisions.

Data science involves using statistical techniques and machine learning algorithms to extract insights and patterns from large datasets.
Data analytics involves analyzing data to understand trends, patterns, and correlations to support decision-making.
Data science is more focused on predictive modeling and building algorithms, while data analytics is more focused on descriptive and diagnostic analysis.
Data scientists often work with unstructured and complex data, while data analysts typically work with structured and organized data.
Data science can involve tasks like data cleaning, feature engineering, and model evaluation, while data analytics focuses more on data visualization and reporting.
Example: Data science can be used to develop a recommendation system for an e-commerce platform, while data analytics can be used to analyze customer behavior and optimize marketing strategies.

Accepted Answer

They are almost same,Data Science seeks to discover new and unique questions that can drive business innovation. In contrast, Data Analysis aims to find solutions to these questions and determine how they can be implemented within an organization to foster data-driven innovation

Digference between data science and data analytics

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