Big Data Services

Yuezhi Big Data service covers data applications, data assets, data platforms and other service capabilities. Based on comprehensive big data and AI capabilities, Yuezhi provides cross-industry and cross-field big data solutions and products services for businesses in finance, government affairs, ToB, etc.

Capability Matrix


Data Asset Service - Data Governance - A large domestic real estate company

Business pain points

1.Management decisions can hardly be made due to the non-unified data standards and differences between statistics and assessment. 

2.Multiple systems maintain the data, and the work for the same type of data is repetitive and with poor timeliness, so the data quality can not be guaranteed.

3.There is no unified control for data, and the smokestack style system construction makes it impossible to share data effectively.


1.In-depth investigation and analysis of the current situation to find data management countermeasures.

2.Establish and improve enterprise-level data governance system (including data management strategy, data standard, management system, management process and management tools).

3.Establish a dual middle platform management mode for business and data, realise a unified data management platform, and provide strong support for creating value.

Benefit value

1.Focus on the customers, through data governance to build data assets centred on people, space and services, to realize data transformation.

2.With the housekeeper as the core starting point, deeply reach the owners, and promote the implementation of value-added services in the project.

3.Taking atomic-design as the starting point, the digital operation is realised through process reform and lean model design, and the overall operational efficiency is improved.

Data Asset Service - Data Governance - A government affairs platform

Business pain points

1. Insufficient governance and application: No competent department for data management, unable to support business applications.

2. Low quality and weak analysis: The data has many incomplete, untimely, and inaccurate problems.

3. Difficulty in integration and multiple standards: Each system needs macroscopic guidance and integration standards.

4, Weak security and difficulty in sharing: The lack of effective data security management has led to data security concerns among various departments, and they dare not share or open.


1. Created a '1+9+N' city-level data governance system with urban characteristics.

2. With the 'data brain platform' as the mainline, it covers three middle platforms (data middle platform, application middle platform, AI middle platform), two enabling platforms (data resource management platform, data open platform) and three systems (data resource management system, standard specification system, safety management system)

3. Formed a closed loop of the whole process of standardised data governance practice of 'gather, communicate, use, and manage'.

Benefit value

1. Build the core capability of the 'data brain', conduct in-depth integration and governance of data, promote the agility and efficiency of smart city construction, and continuously release data value.

2. Promote the innovation and evolution of smart city construction, and use a powerful 'brain' to control it. The concepts of service and middle-platform meet the needs of this unified control.

3. Promote the intensive and unification of smart city construction, realise unified planning, unified standards, unified management, and unified supervision of the whole city, and effectively avoid independent governance, self-contained systems, repeated investment, and repeated construction.

Data Asset Service - Data Analysis - A large domestic bank

Business pain points

1. It takes a long time to verify and analyze the abnormal operation.

2. Poor expansibility of thematic analysis reports.

3. Data analysis is highly dependent on people.

4. Poor timeliness of data acquisition required by leadership decision making. 


1. Establish a data governance system and process (improve work efficiency and data quality).

2. Set up databases for analysis subject and analysis module  (centring on the company's strategic management and business needs).

3. Establish an intelligent operation monitoring system (monitor and act on abnormal indicators).

4. Build an intelligent accounting secretary (develop an intelligent accounting secretary model).

5. Establish a unified platform (unified management, monitoring, and usage) to improve resource utilisation.

Benefit value

1. Improved customer data insight ability (rich graphical presentation tools, interactive data analysis experience, BI mode for all staff), advanced company financial report time by one week and decision time by 20%.

2. Used the data model based on the in-memory Column-oriented Storage engine to significantly improve the performance of data analysis.

3. Completed data authority management solution to solve the authority issue between head office and branches.

4. Improved the level of data intelligence (automatic monitoring, intelligent report, intelligent accounting secretary and other scenarios).

Data Platform Service - Big Data Development - Mobile threat perception

Business pain points

With the development of the mobile Internet, the proportion of mobile devices is increasing rapidly, related security has always been the top priority; Incidents such as phone hijacking and virus attacks occur all the time, and users often don't notice the damage until it's too late.


1. Consume data in Kafka message queue through sparkStreaming, and quickly read Redis database data through API interface for secondary combination calculation.

2. Use sparkStreaming to complete real-time processing, strategy delivery and real-time presentation for all data.

Benefit value

1. Quick response to all kinds of virus invasion, hijacking and other illegal operations that targets mobile device.

2. Ensure the data security of user's mobile devices.

3. From 'discovery after the event' to 'prediction in advance', mobile information security has been greatly improved.

Application Data Service - Data Mining - Customer churn warning

Business pain points

After the loss of high-value customers, the retention cost is too high and the effect is too weak.


1. The database directly processes the data set to reduce the pressure on the model machine.

2. Automatically search for the current optimal parameter and select the optimal model.

3. Visualize the results to ensure high interpretability.

Benefit value

1. Automatic data management and model update, multi-dimensional cost reduction.

2. One-click operation, visualised output process and results.

3. All white-box process, on-site technology empowerment, providing sustainable solutions.

4. Predict further; about ¥6 million in quantifiable gains.

Our Clients