On May 21 and 22, 2018, CDA data analysts conducted a talent training program with the theme of "data mining and application" at Lenovo (Beijing) Company. More than 20 employees of Lenovo (Beijing) Company participated in this event On May 22, the event was a complete success.

Company Introduction

Lenovo Group is an investment of 200, 000 yuan in 1984 by the Institute of Computing Technology of the Chinese Academy of Sciences and was founded by 11 scientific and technological personnel. It is a large enterprise group with diversified development in the information industry in China, and an innovative international technology company . Since 1996, Lenovo ’s computer sales have always ranked first in the Chinese domestic market; in 2004, Lenovo Group acquired the IBM PC (Personal Computer, Personal Computer) business unit; Of PC manufacturers.
As a leader in the global computer market, Lenovo is engaged in the development, manufacture and sale of reliable, safe and easy-to-use technical products and high-quality professional services to help global customers and partners succeed. Lenovo mainly produces desktop computers, servers, notebook computers, printers, handheld computers, motherboards, mobile phones, all-in-one computers and other commodities.

brief introduction

Part 1: The era of big data
1. The origin of big data
2. The relationship between big data and smart phones, perception devices, Internet of Things, social media and cloud computing
3. Successful case of big data application
4. The future of big data
5. Thinking change in the era of big data
6. The application of community big data
7. Mobile big data applications
8. Analysis of public opinion under text data
9. The myth of big data (big data is still a big mistake)
Part 2: Basics of data mining
1. The core key technology of big data-data mining
2. The development of data mining
3. Steps of data mining
4. Industry standard for data mining (CRISP DM amp; SEMMA)
5. Introduction to basic data mining techniques (query tools, statistical techniques, visualization techniques, K-nearest neighbor techniques, etc.)
6. Introduction to advanced data mining techniques (classification, prediction, association rules, sequence patterns, clustering, etc.)
7. Performance Evaluation of Data Mining and Optimization of Number of Customers
8. Problem-oriented data mining analysis process
9. How to get big data? How to start an enterprise data mining project?
10. Future trends in data mining
Part 3: Data mining technology and practical modeling
1. Data Preprocessing
2. Key field / variable mining technology
3. Classification Techniques-Decision Tree
4. Prediction Techniques-Time Series
5. Clustering Techniques – K-Means, Kohonen SOM, Two-Step

Main operation case:
1. Cases of job seekers' future performance pros and cons
2. Listed company financial warning case
3. Catalog sales forecast
4. Discover valuable customer cases
The experience and evaluation of the participating employees
Two days of CDA data mining and sharing, so that our ERP engineers have a deeper understanding of data mining. Mr. Li, who is highly technical and experienced in the industry, explained the data application, practical techniques and case studies in an in-depth way, built a perfect knowledge structure for the students, and laid a solid foundation for us to analyze massive business data. At this time, the company and the sector are in transition. We hope that through continuous self-improvement and learning, we will use the power of big data analysis and prediction to accelerate sector transformation, help the company's development, and increase corporate market profits. At the same time, I also hope that there will be more cooperation with CDA data analysts in the special subject courses.