Data Glossary Lab

Descriptive analytics is the process of examining historical data to understand what happened in your business and why it happened. It's the foundation of data analysis—the autopsy that reveals patterns, trends, and insights buried in your numbers.

A dashboard is your business's command center—a single screen that consolidates critical metrics, KPIs, and data points into digestible visual displays.

A data pipeline is the digital circulatory system of the modern enterprise.

Deep Learning is a subset of artificial intelligence that uses multi-layered artificial neural networks to process and learn from complex, unstructured data including images, audio, video, and text.

Data Analytics is the systematic process of examining, cleaning, transforming, and interpreting data to discover meaningful patterns, extract actionable insights, and support evidence-based decision-making across organisations.

Data Engineering is the discipline of designing, building, and maintaining robust data infrastructure and pipelines that enable organisations to collect, store, process, and deliver data reliably at scale.https://bigblue.academy/en/data-engineering-bootcamp

Data Science extracts insights from data using statistics, programming, and machine learning.

Data Visualization is the process of transforming raw data into visual representations like charts, graphs, maps, and interactive dashboards for easy understanding and quick decision-making.