Data analytics involves collecting, cleaning, processing, and interpreting data to identify trends, patterns, and actionable insights. It helps businesses understand how users behave, which products perform best, and where opportunities for growth exist. Data analytics can include descriptive, diagnostic, predictive, and prescriptive techniques. Organizations use analytics to improve decision-making, forecast outcomes, optimize experiences, and strengthen performance across marketing, product, finance, and operations.
Glossary · D
Data analytics
The process of collecting, analyzing, and interpreting data to uncover patterns, trends, and insights that guide business decisions.
More terms starting with D
- DashboardA visual interface that displays key metrics, analytics, and performance indicators in real time for easy monitoring and decision-making.
- Data migrationThe process of transferring data from one system, platform, or storage type to another, often during upgrades or software transitions.
- DatabaseAn organized collection of structured data stored electronically, designed for efficient retrieval, management, and updating.
- DevOpsA set of practices that combines software development and IT operations to shorten the development lifecycle and deliver high-quality software.
- DocumentationWritten materials that explain how software works, including user guides, API references, and technical specifications.