What Is Data Science?

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’s used to uncover actionable insights in large datasets, and to inform business strategy and planning. The job requires a combination of technical abilities, including up-front data preparation, mining and analysis, along with excellent leadership and www.virtualdatanow.net communication skills to share results with other people.

Data scientists are often innovative and inquisitive, as well as passionate about their work. They relish intellectually stimulating tasks which require obtaining complex readings from data and discovering new insights. A large portion of them are “data nerds” who cannot resist investigating and analyzing “truths” that lie below the surface.

The first step of the data science process is collecting raw data through various methods and sources, such as databases, spreadsheets, application program interface (API) and images or videos. Processing includes removing missing values and normalising numerical features and identifying patterns and trends, and splitting the data up into training and test sets for model evaluation.

Due to factors such as volume, velocity and complexity, it can be difficult to mine the data and identify useful insights. Using established methods and techniques for data analysis is essential. Regression analysis, as an example allows you to see how dependent and independent variables interact through a fitting linear equation, and classification algorithms such as Decision Trees and t-Distributed Stochastic Neighbour Embedding aid in reducing the dimensions of your data and identify relevant clusters.