What Is Data Science?

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Data science is a subject that blends math and statistics with specialized programming advanced analytics methods like machine-learning, statistical research, and predictive modeling. It is used to find useful insights from large datasets, and to inform business strategy and planning. The job requires a mixture of technical skills, including upfront data preparation as well as mining and analysis and also an ability to communicate effectively and to share results with others.

Data scientists are usually interested, creative, and passionate about what they do. They love intellectually stimulating challenges that involve deriving complex reads from data, and uncovering new insights. Many of them are self-proclaimed “data geeks” who are not able to resist when it comes to examining and looking into the “truth” that lies beneath the surface.

The first step of the data science process involves collecting raw data through diverse methods and sources. These include spreadsheets, databases, applications program interfaces (API) along with images and videos. Preprocessing includes handling missing values and adjusting numerical features to normalize them, identifying trends and patterns and dividing the data up into training and test sets to evaluate models.

Due to factors like volume and complexity, it is often difficult to delve into the data and find relevant insights. Using established methods and techniques to analyze data is crucial. Regression analysis aids in understanding how dependent and independent variables relate through a fitted linear formula, while classification algorithms such as Decision Trees and tDistributed stochastic neighbour embedding aid in reducing the data dimensions and identify relevant groups.