数据挖掘：数据挖掘是分析大量数据以发现关系、设计和洞察力的方法。 Witten 和 Eibeme 同意这些设计必须“有意义，因为它们带来了一些优势，通常是财务优势。”数据挖掘中的数据通常是定量的，特别是当我们考虑到社交媒体在很长一段时间后提供的数据呈指数级发展时，即大数据。
数据可视化：数据可视化是在图表、图表、图片等框架内的数据表示。这些是作为信息的可视化表示。选择查看外部显示的分析结果会有所不同，因此他们可以以类似的方式工作，并可以处理麻烦的概念或识别现代设计。
下表列出了数据挖掘和数据可视化之间的差异：
| Data Mining | Data Visualization |
|---|---|
| Searches and produces a reasonable result from huge information chunks. | Gives a basic diagram of complex information |
| This is often has diverse applications and favored for web search engines. | Preferred for information determining and forecasts |
| Data mining Comes beneath data science. | Data Visualization Comes beneath the range of data science |
| Worked with web computer program frameworks or applications . | Supports and works way better in complex data examinations and applications |
| Modern innovation but underdeveloped. | More valuable in genuine time information estimating |
| Numerous algorithms exist in utilizing data mining. | No require of utilizing any algorithms |
| Runs on any web-enabled stage or with any applications . | Irrespective of equipment or computer program, it gives visual data |
| Application is display satellite data information, research results information, scientifically studied data | The applications of the Information mining are web search engines, retail, money related and banking businesses, government organizations etc. |