📜  商业智能和数据挖掘之间的区别

📅  最后修改于: 2021-09-14 02:38:33             🧑  作者: Mango

1.商业智能:
商业智能 (BI) 一词暗指用于收集、集成、检查和引入业务数据的进步、应用和磨练。 Commerce Insights 的目的是支持卓越的贸易选择。基本上,Trade Insights 框架是数据驱动的决策支持系统 (DSS)。商业智能现在不时与简报、报告和查询工具以及官方数据框架进行交易。

商业智能框架提供真实的、当前的和有先见之明的商业运营,最常用的是利用已组装到信息库或信息商店中的信息,有时还使用运营信息。

2. 数据挖掘:
从庞大的数据库中提取被掩盖的先见之明的数据可能是一项强大的现代创新,具有巨大的潜力,可以帮助公司专注于其数据仓库中最重要的数据。它包含一个巨大的范围是小的以及巨大的组织。数据挖掘本质上是在与信息仓库相反的过程中使用的。通过分析一家公司的客户信息,数据挖掘设备可以构建一个先见之明,告诉你哪些客户是幸运的还是不幸的。

商业智能和数据挖掘的区别:

Business Intelligence Data Mining
Changing over raw information into valuable data for business. Designed to investigate information and discover the arrangement for an issue in business.
Data-driven makes a difference in choice making for a business. Finds answers to an issue or a issue in trade.
Expansive Datasets processed on dimensional / social databases Small datasets handled on little parcel of data.
Volumetric in nature and display the exact result utilizing visualizations. Uses calculations to distinguish precise designs for an issue and distinguishes the daze spots.
Dashboards and Reports spoken to by charts and charts with KPI’s. Identifies the arrangement for an issue to be spoken to as one of the KPI’s in Dashboards or reports.
Depends on small-scale of past information, there’s no intelligence involved; administration needs to take the choice based on the information. Focused on a specific issue in trade on small-scale information utilizing calculations to discover the arrangement.
Appears cost esteem, benefit, add up to fetched, etc. as KPI’s. Identifies arrangement for an issue making modern KPI’s for BI
Business Intelligence makes a difference in Decision-making . Data Mining will unravel a specific issue and contribute to decision-making.
Business Intelligence consists of creation, aggregation, analysis and visualization of data. Data Mining consists of cleaning, combining, transforming and interpretation of data.