Data Science: Machine Learning, Data Mining, BI, Business Analytics

What is Data Science?

Data science is the process of collecting, processing, understanding, and communicating meaning from data. As a field of study, data science involves programming, statistics, algorithms, and visualizations. It also involves effectively conveying meaning and value from data.

The data science lifecycle involves business or organization-level understanding of goals, what data is available, data preparation, data analysis, data modeling, data evaluation, and model deployment (or communication of results). Following the data life cycle is a good way of organizing goals for an organization or business while getting the best value from data resources.

Data scientists are necessary for almost any modern business and require high technical and math skills. Data scientists must be able to analyze data and make meaning from it complexly. Data scientists can answer questions and create possible solutions to existing organizational problems.

Data science requires skills found in similar computer science roles, like programming and math. Additionally, data scientists must be creative, know how to build models, and have good communication skills to communicate results effectively to a team. Data science uses tools like SQL, GitHub, R, Python, and many others. Data science is a high-demand career, and the demand for people in this role is only expected to grow.

While being a data scientist can be a demanding role, one can learn this field in under a year. This experience takes dedicated study time but is manageable for the motivated learner. By committing to studying data science with the same hours as a full-time job, one can learn the basics to become an entry-level data scientist.