andmeteadus

Andmeteadus, or data science in Estonian, is the interdisciplinary field that focuses on extracting knowledge and insights from data. It combines statistics, computer science, and domain expertise to analyze structured and unstructured data, build predictive models, and inform decision-making.

Core components include data collection and cleaning, exploration and visualization, statistical analysis, machine learning, and the deployment and monitoring of models. It also involves data governance, quality assurance, and consideration of ethical, legal, and social implications.

Typical workflow encompasses problem formulation, data acquisition, preprocessing and cleaning, exploratory analysis, model building and evaluation, interpretation of results, and deployment to production with ongoing monitoring and maintenance.

Tools and techniques include programming languages such as Python and R, SQL for data querying, and libraries (e.g., for machine learning, visualization). It also uses database systems, data pipelines, and sometimes big data platforms for large-scale analytics.

Applications span business analytics, finance, healthcare, marketing, science, and public policy. Education and career paths emphasize statistics, mathematics, programming, data wrangling, and domain knowledge, often through university degrees or bootcamps. The field continues to evolve with emphasis on reproducibility, transparency, privacy, and fairness in algorithms.