The client is a comprehensive company approved by the China Securities Regulatory Commission (CSRC) to engage in futures business. It primarily engages in commodity futures brokerage, financial futures brokerage, futures investment consulting, asset management, and other businesses. It holds membership status at the Zhengzhou Commodity Exchange, Dalian Commodity Exchange, Shanghai Futures Exchange, China Financial Futures Exchange, Guangzhou Futures Exchange, and Shanghai International Energy Exchange Center. The company operates one risk management subsidiary and over twenty branches covering major cities and regions across China. As a vital component of the group's development strategy, the company is committed to promoting the development of the real economy and meeting national wealth management needs. Leveraging the strong resource advantages of its shareholders, it aims to build a derivatives investment bank and become a top-tier comprehensive derivatives service platform in China.
Project Background
The client faces the following challenges in CMDB management:
- Legacy Excel-based manual ledger maintenance leads to fragmented data management and inconsistent records.
- With the adoption of cloud and container technologies, the volume of configuration data requiring governance has surged dramatically, resulting in high manual maintenance costs.
- Data accuracy in the CMDB cannot be guaranteed.
Project Solution
- Establish unified operations data standards: Define standardized data models for all physical assets and logical resources in the CMDB, including formats, collection frequency, storage methods, and relationships, creating a full lifecycle data modeling standard.
- Strengthen operations data quality management: Implement agentless auto-discovery technology in the CMDB to automate discovery, identification, collection, and processing of over 90% of resource configuration data.
Establish a CMDB data quality assessment system and control processes. Ensure data accuracy, completeness, and timeliness through automated cleansing, validation, and monitoring mechanisms. - Drive value realization from operations data: Targeting key IT operations scenarios like monitoring management and asset management, deliver servitized CMDB-governed data.
Integrate resource configuration data into operational workflows, enabling data flow within and between scenarios.
Demonstrate the value of configuration data to enhance automation, reduce incident response times, and provide data-driven support for business continuity assurance, risk prevention, and strategic decision-making.