[E-Commerce] 1.E-Commerce Data Analysis
#ICT# #IOT#

Lesson Code: TCEN2025H034

Clicks:
Academic Hours
2.10hours
Publish Date
Dec 2025

Lecturer

1. Lecturer FU MaoweiSichuan Vocational College of Information Technology

General Introduction
This course is a foundational subject for majors such as E-Commerce and related fields, focusing on developing students’ data analysis and decision-making abilities.
It mainly teaches the basic concepts and methods of market data analysis, operation data analysis, and product data analysis.

This Course is for
1. Familiarizing trainees with the content, methods, tools and processes of industry data, customer data, product data, and operation data analysis.
2. Mastering the common models and analysis methods of e-commerce data analysis for trainees.
3. Enabling trainees to support the formulation and improvement of enterprise strategic goals based on the results of e-commerce data analysis.
4. Equipping trainees with the core concepts and processes of data-driven operations, while helping them understand the application scenarios and tool classifications of e-commerce data-driven operations.
5. Helping trainees grasp the common data collection channels and their characteristics in e-commerce data analysis, as well as understand the functions, advantages, disadvantages and applicable scenarios of mainstream data collection tools.
6. Guiding trainees to master the core structure and writing logic of data analysis reports, and enabling them to independently compile complete data analysis reports.

Learning Materials

1. Corresponding PPT
2. Online Course Video
3. Simulation Question Banks

Recognized By

Benefits of Learning

1. Understanding and proficiently applying basic knowledge such as descriptive statistics, inferential statistics, and probability to interpret the distribution, trends, and correlations of e-commerce data.
2. Being able to identify opportunities and risks from massive amounts of data, gain insights into user behavior and market trends, formulate actionable optimization suggestions, and drive business decisions.
3. Possessing strong logical reasoning abilities to construct rigorous analysis frameworks.
4. Being skilled at converting complex analysis results into clear and understandable business language (charts, reports, verbal presentations) for effective communication of conclusions.
5. Familiarizing oneself with the core business processes, key indicators, and core scenarios of e-commerce to connect data with business operations..

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