What Is Data Science?

Data science is like the magic behind the scenes that helps social media sites to understand your preferences and create their content to keep you on the edge. Airlines employ it to predict weather patterns, analyze the data collected by sensors from aircraft and rockets, and increase the safety of flights.

Understanding the significance of data is the first step towards becoming a data scientist. The foundational knowledge of programming (Python and R are the most commonly used) and statistics and machine learning algorithms and data visualization are essential for solving real-world issues.

Data Preparation

The second ability is to prepare raw data. This includes tasks like handling missing data, normalising features, encoding categorical variables, and dividing datasets into test and training sets to evaluate models. This ensures a high-quality dataset that is ready for analytical processing.

Data scientists then employ a variety of statistical methods to discover patterns, trends and other insights. These include descriptive analytics, diagnostic analytics, prescriptive analytics and predictive analytics. Descriptive analytics summarizes a dataset in an attractive and easily accessible format, like median mode, mean, standard deviation and variance. This lets users make informed decisions using their findings. Diagnostic analytics leverages previous data to predict future outcomes. This is used by credit card companies to forecast the risk of default. Predictive analytics employs patterns to predict future trends such as sales and price of stock.

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