Data science is a multidisciplinary field that uses a combination of statistics, computer science, and domain-specific knowledge to extract meaningful insights and knowledge from data. The main goal of data science is to transform raw data into actionable insights, predictions, and decisions. Here's a breakdown of what data science involves:
1. Data Collection & Acquisition
What it involves: Gathering data from various sources like databases, web scraping, IoT sensors, APIs, surveys, or existing datasets.
Purpose: To have relevant and sufficient data to work with, which is essential for building models and making decisions.
2. Data Cleaning & Preprocessing
What it involves: Preparing the data for analysis by handling missing values, removing outliers, correcting errors, and transforming data into a usable format.
Purpose: Raw data is often noisy and incomplete, so cleaning and preprocessing ensures better analysis and model performance.
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