Data Glossary Lab

ELT (extract, load, transform) is a data pipeline system designed by data engineers, an alternative to the traditional approach ETL (extract, transform, load). Before applying any transformation, the raw data is extracted from source systems and loaded directly into a data lake or data warehouse.

ETL (extract, transform, load) is a data pipeline system designed by data engineers. The data is extracted from multiple sources, transformed from its raw form into a proper format to be consistent with the data from other sources, and loaded into the target data warehouse.

Evaluation Metrics are a collection of statistical measurements used to estimate the performance and quality of a statistical or machine learning model. While training a model is about learning patterns, evaluation is about objective validation.

Explainable AI (often abbreviated as XAI) represents a set of processes, methods, and techniques within the field of machine learning that allows human operators to comprehend and trace the decision-making processes of artificial intelligence systems.

Exploratory Data Analysis is the forensic investigation phase of data science. Before building models or making predictions, you interrogate your data—probing for patterns, hunting anomalies, testing assumptions.