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data asset management system project
Mininglamp Technology has built for customer banks a next-generation data asset management system tailored to financial institutions. Based on the business-oriented data asset catalog and full-graph and global lineage and supported by the knowledge graph, machine learning, and natural language processing (NLP) technology, the system allows enterprise-level data to be managed and shared in customer banks.
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丸美DMP系统升级,打造企业数字资产体系
基于数据资产统一管理,女性目标群体触达率 90%+
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上海家化搭建DMP实现精细化运营
基于 DMP 优化数字营销效果及加速后端销售转化
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真正触达意向购车人群,CTR提升133%
基于明略DMP和Serving 工具,实现在线投放精细化管理
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广汽菲克搭建DMP,全面提升营销ROI
打通全域数据,完善用户画像。基于DMP 留资成本 CPSL 降低71%
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The intelligent train O&M system helps a city's subway system effectively improve operation efficiency.
The increasing number of trains and extended operation time put the train O&M under bigger pressure. Our system can keep track of a train's mainline status, as well as the condition and faults of key equipment in real-time, and conduct data analysis based on a large amount of equipment status data.
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data asset management system project
Mininglamp Technology has built for customer banks a next-generation data asset management system tailored to financial institutions. Based on the business-oriented data asset catalog and full-graph and global lineage and supported by the knowledge graph, machine learning, and natural language processing (NLP) technology, the system allows enterprise-level data to be managed and shared in customer banks.
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基于知识图谱的智能审计项目
明略科技为客户银行基于全行全量数据构建成“企业、个人、机构、账户、交易、以及行为数据”,规模达十亿点百亿边的知识图谱数据库。通过采用复杂网络、图计算等大数据算法,实现海量结构化与非结构化数据的分析和探索。
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Maintenance planning based on personnel's workload capacity helps the State Grid substation maintenance teams improve management precision;
Our solution helps to solve the problems such as unbalanced work planning, excessive reliance on manual calculation, high effort input, and high fault tolerance; realize a better assignment of tasks to staff to eliminate the reliance on manual effort in resource allocation; and quantize the staff workload to provide a basis for performance evaluation.
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Fault knowledge bases built for substations increases the incident recognition rate and reduces maintenance costs
With the substation fault knowledge bases, the reliance on the monitoring alarm window is reduced to avoid the huge pressure on the monitoring screen in case of frequent faults. The problems such as insufficient recognition of alarm signals, inaccurate analysis, and non-standard operations have been solved, with the efficiency of processing alarm signals in real time increased greatly.
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Intelligent fault diagnosis is realized at the State Grid substation maintenance center to eliminate the need for manual interference.
The time for searching for fault information is shortened from a few minutes to less than 1 minute. Fault forms are generated with just one click to reduce the workload of information collection by 85% for a single fault.
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O&M prediction and risk evaluation are conducted through intelligent data analysis to reduce the O&M cost of steel manufacturing;
When building a PHM model, as opposed to the conventional method, our solution allows the equipment to obtain offline data through intelligent data analysis, without the need to train the model offline before putting it into use. This improves the model updating and iteration efficiency, and makes the response to equipment updates faster.
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