Data science involves analyzing complex data to extract insights and inform decision-making. Key terminology in data science includes terms like data wrangling, the process of cleaning and organizing raw data, and data visualization, which turns data into graphs and charts to make patterns easier to understand. Machine learning and statistical models are also crucial for predicting future outcomes based on historical data.
Other important terms include big data, which refers to large datasets that require advanced tools to process, and A/B testing, a method for comparing two versions of a webpage or app to determine which performs better. Understanding these terms is essential for anyone working with data or aiming to leverage data science techniques.