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Data science is the magic behind the scenes that helps social media top article sites to understand your interests and tailor their content to keep you on the edge. It is also utilized by airlines to forecast weather patterns and analyze sensor data on aircraft and rockets to improve flight safety and efficiency.

Data scientists must first comprehend the value of their data. Solving real-world problems requires a solid background in programming (Python or R are the most popular) as well as statistics machine-learning algorithms, data visualisation.

Data Preparation

The other key ability is to prepare raw data for analysis. This includes things like handling missing data or normalizing features. Also, it involves encoding categorical variable and splitting datasets in test and training sets to evaluate models. This ensures that the dataset is of the highest quality and ready to be analysed.

Next, data scientists use various statistical methods to identify trends, patterns, and insights. These include descriptive analytics as well as diagnostic analytics, prescriptive analytics and predictive analytics. Descriptive analytics provide a concise summary of a data set in visually appealing and easily understandable formats such as mean mode, median, standard deviation, and variance. This allows users to make informed decisions based on their findings. Diagnostic analytics leverages previous data to predict future outcomes. A credit card company uses this to predict customer default risk, for instance. Predictive analytics utilizes patterns to predict future trends, such as sales and stock prices.