Data Glossary Lab

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

Data Analysis (DA) is the technical discipline focused on cleaning, transforming, visualizing, and exploring data to extract meaningful patterns and insights.

A Data Analyst analyzes data and reports insights from their analysis, often using a combination of coding and non-coding tools in order to support decision-making.

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.

A Data Consumer is an individual or department that uses the data insights, reports, and dashboards provided by data professionals to make informed business decisions.

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 Enrichment is the process of enhancing, refining, and augmenting raw, internal data with additional information from external sources.

Data ingestion is the "digital intake system" of an AI infrastructure, representing the critical first step in the data lifecycle where information is moved from various sources into a storage or processing environment.

Data mining is the process of collecting relevant data from various sources, cleaning and transforming it to the right format, detecting and extracting meaningful hidden trends, patterns, and interconnections between the data, and communicating actionable insights to help the organization make data-driven decisions and develop better strategies