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Introduction

The Lab is designed for students majoring in big data technology and related fields. It provides practical project resources and supporting teaching platforms based on the latest big data application technologies and mainstream tools in the financial industry. The Lab is designed to meet the typical job tasks and professional technical abilities required for big data technology talent in the financial industry. It aims to cultivate the core competencies of big data collection and processing, big data analysis and visualization, and big data implementation and maintenance for various positions. Through project practice, students will become proficient in using technologies and tools such as JDK, Hudi, Flink, FlinkCDC, Kafka, Hive, Spark, Hadoop, Mysql, SpringBoot, Vue, Miniconda, Python, TensorFlow, Nginx, FineBI, which will help enhance their problem-solving ability and innovation ability.

Enterprise positions: Big Data Development Engineer, Big Data Collection and Processing Engineer, Big Data Analysis and Visualization Engineer, Big Data Implementation and Maintenance Engineer

Applicable majors: college majors in big data technology and related fields. Project Products: Financial Big Data Collection and Processing Practice Project (Financial Big Data Real-time and Offline Processing System), Financial Big Data Analysis and Visualization Practice Project (Financial Credit Analysis and Data Visualization System), Financial Big Data Implementation and Maintenance Practice Project (Hudi Financial Big Data Platform Deployment), Big Data Full Stack Technology Integrated Practice Project (Financial Big Data Statistical Analysis Platform)

Project Courses: a number of post level and post group level projects based on the application of big data in the transportation industry, including big data collection and processing, big data analysis and visualization, big data deployment and operation and maintenance training

Applicable scenarios: professional teaching, integrated training, competition training.

Industry-oriented and covering cutting-edge technologies

Based on the latest Hudi data lake technology in the industry, the real-time data lake storage mode is used to provide more efficient support for big data analysis and mining, using Python, Pyecharts and FineBI self-service data visualization tools to achieve data visualization; using SpringBoot and React frameworks to realize the web display of data visualization dashboards, training students' big data full stack development skills.

Unique industrial-level cases, teaching-based disassembly

Based on the TOPCARES educational methodology of Neusoft's unique feature, the industrial-level project is decomposed into a progressive project system, from simple to complex, helping students gradually improve their practical skills. We provide 3 position-level and 1 position cluster-level projects, progressively training different job skills.