Data science integrates various tools and techniques to extract insights from data. Key programming languages include Python and R, known for their powerful libraries like Pandas and ggplot2. Data visualization tools, such as Tableau and Matplotlib, help communicate findings effectively. Machine learning frameworks like TensorFlow and Scikit-learn enable predictive modeling. SQL is crucial for database management, while Jupyter Notebooks provide an interactive coding environment. Techniques such as data cleaning, exploratory data analysis, and feature engineering are foundational for successful projects. Mastering these tools and techniques empowers data scientists to turn raw data into actionable insights.