Data science is an interdisciplinary field that combines mathematics, statistics, programming, and domain expertise to extract meaningful insights from data. It involves several key stages^1,2,3: 1. **Data Collection**: Gathering data from various sources, including databases, web scraping, and real-time streaming. 2. **Data Preparation**: Cleaning and transforming raw data to ensure quality and consistency. 3. **Data Analysis**: Using statistical methods and algorithms to explore and model the data. 4. **Visualization**: Presenting insights through charts, graphs, and other visual tools to make the data understandable. 5. **Decision Making**: Applying the insights to guide strategic decisions and solve real-world problems. Data science is crucial in many industries, from healthcare to finance, as it helps organizations make data-driven decisions and uncover hidden patterns.⁴ Sources - Based on Copilot Query (September 20, 2024). [1](https://www.ibm.com/topics/data-science) [2](https://www.datacamp.com/blog/what-is-data-science-the-definitive-guide). [3](https://en.wikipedia.org/wiki/Data_science). [4](https://www.ibm.com/topics/data-science) Resources - [Data Science Desktop Survival Guide (togaware.com)](https://onepager.togaware.com/) *** 2024 cloudedknowledge.net