Datajaset

Datajaset is a term that may be used to refer to a dataset, a structured collection of data selected for analysis. In data science, a dataset consists of instances (rows) and attributes (columns). Each instance represents an observation, and each attribute describes a property of that observation. In supervised learning, datasets often include labels or target values that are used to train models.

Datasets can be structured, unstructured, or semi-structured. They are stored in formats such as CSV, JSON, Parquet, or in relational databases. A typical dataset is partitioned into subsets for training, validation, and testing to evaluate model performance. Metadata, schemas, and data dictionaries describe the meaning and types of the attributes.

Datajaset creation usually involves data collection, cleaning, normalization, handling missing values, and, when appropriate, feature engineering. Data quality, provenance, and documentation are important for reproducibility. Privacy and ethics considerations include de-identification and careful handling of sensitive information, along with licensing that governs data use and sharing.

Common examples of datasets include tabular data from surveys or transactions, time-series data from sensors, and unstructured data such as text, images, or audio used in machine learning. Open datasets published by organizations enable benchmarking and collaborative research, while proprietary datasets support commercial analytics.

See also: dataset, data science, machine learning, data governance.