Data science is a multidisciplinary field that involves extracting insights and knowledge from structured and unstructured data using various techniques, algorithms, and tools. Here's a breakdown of some key aspects of data science:

Data Collection: Data scientists gather data from various sources, including databases, APIs, sensors, social media, and more. This data can be in structured formats like databases or spreadsheets, or unstructured formats like text documents, images, or videos.

Data Cleaning and Preprocessing: Raw data often contains errors, missing values, inconsistencies, and noise. Data scientists preprocess and clean the data to make it suitable for analysis. This involves tasks like removing duplicates, handling missing values, normalization, and feature scaling.

Exploratory Data Analysis (EDA): EDA involves exploring the data to understand its underlying patterns, distributions, and relationships. Data visualization techniques like histograms, scatter plots, and heatmaps are commonly used to gain insights into the data.
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