数据科学：数据科学是一个领域或领域，它包括并涉及处理大量数据，并将其用于构建预测性、规范性和规范性分析模型。它是关于挖掘、捕获、（构建模型）分析（验证模型）和利用数据（部署最佳模型）。
它是数据和计算的交集。它融合了计算机科学、商业和统计学领域。
数据挖掘：数据挖掘是一种从庞大的数据集/库中提取重要和重要信息和知识的技术。它通过仔细提取、审查和处理大量数据以找出对业务很重要的模式和相互关系来获得洞察力。它类似于从岩石和沙子中提取黄金的金矿开采。
下表列出了数据科学和数据挖掘之间的差异：
| S.No. | Data Science | Data Mining |
|---|---|---|
| 1 | Data Science is an area. | Data Mining is a technique. |
| 2 | It is about collection, processing, analyzing and utilizing of data into various operations. It is more conceptual. | It is about extracting the vital and valuable information from the data. |
| 3 | It is a field of study just like the Computer Science, Applied Statistics or Applied Mathematics. | It is a technique which is a part of the Knowledge Discovery in Data Base processes (KDD). |
| 4 | The goal is to build data-dominant products for a venture. | The goal is to make data more vital and usable i.e. by extracting only important information. |
| 5 | It deals with the all types of data i.e. structured, unstructured or semi-structured. | It mainly deals with the structured forms of the data. |
| 6 | It is a super set of Data Mining as data science consists of Data scrapping, cleaning, visualization, statistics and many more techniques. | It is a sub set of Data Science as mining activities which is in a pipeline of the Data science. |
| 7 | It is mainly used for scientific purposes. | It is mainly used for business purposes. |
| 8 | It broadly focuses on the science of the data. | It is more involved with the processes. |