数据分析的目的是把隐藏在一大批看来杂乱无章的数据中的信息集中和提炼出来，从而找出所研究对象的内在规律。在实际应用中，数据分析可帮助人们做出判断，以便采取适当行动。数据分析是有组织有目的地收集数据、分析数据，使之成为信息的过程。总的来说，数据分析就是收集和整理数据以得出有用结论的过程，而在这其中将涉及到大量统计学知识的应用。商业分析指的是对方案进行经济效益分析，从财务上进一步判断它是否符合企业目标。如果符合，产品概念就可进入产品研制阶段了。 包括审视预计的销售额、成本和利润是否达到公司预计目标;如达到，则此产品概念才能进一步发展到产品开发阶段。可从商业或消费统计公告中查到特定商品的零售额、有效购买收入、总的零售额等资料。
如何有效的将数据进行收集统计整理，以便完善后续分析的结构，得出准确的分析结果，其中数据统计的准确性和全面性显得至关重要。在本门课程中，学生将会在教授的带领下学习到统计学的相关基础知识，涉及到具体的理论知识点和相关的应用方法，让学生能够对统计学的知识较深的印象，而后将其具体应用到数据分析的实例中来帮助学生加深理解。
The purpose of data analysis is to concentrate and extract the information hidden in a large number of seemingly disorganized data, so as to find out the internal law of the object of study. In practice, data analysis can help people make judgments so that appropriate actions can be taken. Data analysis is an organized and purposeful process of collecting data, analyzing data, and making it into information. In general, data analysis is the process of collecting and organizing data in order to draw useful conclusions, which involves the application of a great deal of statistical knowledge.Business analysis refers to the economic benefit analysis of the scheme to further judge whether it is in line with the business objectives financially. If so, the product concept can enter the product development stage. This includes examining whether projected sales, costs, and profits are meeting the company's projected goals; If achieved, the product concept can be further developed to the product development stage. Retail sales, effective purchase income, total retail sales, etc., for specific items can be found in commercial or consumer statistics bulletins.
In order to improve the structure of subsequent analysis and get accurate analysis results, the accuracy and comprehensiveness of data statistics are crucial. In this course, under the guidance of the professor, students will learn the relevant basic knowledge of statistics, involving specific theoretical knowledge points and relevant application methods, so that students can have a deep impression on the knowledge of statistics, and then apply it to the examples of data analysis to help students deepen their understanding.