Data science is the magic behind the workings that helps social media sites understand your interests and tailor content to keep you interested. Airlines use it to forecast weather patterns, analyze the data from sensors on aircraft as well as rockets and enhance the safety of flights.
Data scientists must first comprehend the value of their data. To solve real-world problems, you need an understanding of programming (Python or R are the most popular) and statistics, machine-learning algorithms, and visualisation of data.
Data Preparation
The second talent is the ability to prepare raw data. This includes tasks such as handling missing data or normalizing features. Also, it involves encoding categorical variables as well as splitting data in training and test sets to test models. This ensures that the data is of a high standard and is ready to be analysed.
Then, data scientists employ a range of statistical techniques to find patterns, trends and patterns. These include descriptive analytics, diagnostic analytics, prescriptive analytics and predictive analytics. Descriptive analytics provide a concise summary of a collection of data using visually appealing and easily understandable formats such as mean mode, median, standard deviation and variance. This lets users make informed decisions based on their findings. Diagnostic analytics makes use of data from the past to predict what will happen in the near future. A credit card company utilizes this technique to predict default risk, for instance. Predictive analytics utilizes patterns to predict future trends such as stock prices and sales.