[Big Data Analysis and Applications] 3.Business Data Analytics
#ICT# #IOT#

Lesson Code: TCEN2026I032

Clicks:
Academic Hours
4.70hours
Publish Date
Oct 2026

Lecturer

1. Lecturer ZHONG MingGuangxi Technological College of Machinery and Electricity

2. Lecturer SHI JiayongGuangxi Technological College of Machinery and Electricity

3. Lecturer SU HongxingGuangxi Technological College of Machinery and Electricity

4. Lecturer MA XiaoyuanGuangxi Technological College of Machinery and Electricity

5. Lecturer WANG JieweiGuangxi Technological College of Machinery and Electricity

6. Lecturer LI WanyuGuangxi Technological College of Machinery and Electricity

General Introduction
This course focuses on the complete cycle of “business problems-data-insights-decision-making,” providing systematic training for students to develop the mindset and skills needed to solve real business problems through data. By enabling students to understand how to
translate business needs into analytical tasks and derive actionable insights, the course aims to cultivate well-rounded business data analysts who possess strong business understanding, solid technical capabilities, and effective communication skills.

This Course is for
1. Enabling trainees to master the fundamental concepts of data analysis and to become familiar with methods for data cleaning, data analysis, and data visualization.
2. Enabling trainees to propose and validate data-driven marketing and operational optimization strategies.
3. Enabling trainees to develop a data-driven decision-making mindset and enhance business insight.

Learning Materials

1. Corresponding PowerPoint Slides
2. Online Course Video
3. Simulation Question Bank

Recognized By

Benefits of Learning

1. Being able to adhere to data compliance standards and complete business requirement analysis, as well as design and implement data collection plans.
2. Having the capability to clean, transform, merge, and store raw data in accordance with data quality standards.
3. Being able to perform data computation, analysis, and visualization for business scenarios such as marketing, customer insights, product evaluation, operations, sales, and supply chain management.
4. Being able to identify data anomalies, locate their root causes, and propose actionable business improvement recommendations.
5. Having the ability to document analytical processes and results, prepare data analysis reports that connect background, methodology, insights, and recommendations through a coherent business storyline, providing actionable decision support for management.

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