Introduction
The Big Data Lab
for Telecommunications at Neusoft is based on the accumulated knowledge assets
of the company's big data projects in the telecommunications industry. It aims
to provide the following practical teaching scenarios and resource support for
college teachers and students: training in the design and implementation of key
functional modules of big data real-time and offline processing systems, design
and implementation of big data processing, analysis and mining, and data
visualization, familiarity with digital telecommunications business, mastery of
the mainstream technologies, tools, processes and methods for digital telecommunications
industry integration applications, understanding of the business meaning of
telecommunications data, and enhancement of problem-solving ability and
innovation capacity cultivation.
Corporate positions: Big Data Development Engineer, Big Data Data Collection and Processing
Engineer, Big Data Analysis and Visualization Engineer, Big Data Implementation
and Maintenance Engineer
Applicable majors: Big Data Technology and other related majors in colleges and universities
Project products: multiple post level and post group level projects based on the application of telecom big data 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
Feature
Industry-aligned
and covering cutting-edge technologies
By building an
end-to-end data collection and transmission process, including business data
extraction, Hive data warehouse creation, and real-time telecom log collection
and transmission, the project provides powerful data processing and analysis
tools for telecom operators. On the data analysis level, the project uses Kylin
technology to build Cube cubes, enabling multi-dimensional OLAP analysis by
correlating multiple data tables from different dimensions, accelerating the
speed of complex queries and report generation. At the same time, it leverages
the Flink real-time computing engine to collect, process, store, and analyze
telecom logs in real time, enabling user behavior analysis. On the data storage
front, the project builds a large-scale data storage system, including
distributed storage and relational databases, to store various telecom data and
achieve data synchronization and integration. The project uses the Logstash
tool to efficiently synchronize MySQL data to Elasticsearch to ensure data accuracy
and real-time, training students' big data full-stack development skills.
Industry-level case
features Teaching-based disassembly
Based on the unique
TOPCARES educational methodology of Neusoft, the project disassembles the
industrial-level project into a progressive project system, from easy to
difficult, helping students gradually exercise and improve their practical
skills. It provides 3 position-level and 1 position cluster-level projects,
training students' incremental skills for different positions.