Qlik > 实例探究 > QlikViewCustomer Snapshot——Chongqing Shanshui Urban Tourism Development Ltd

QlikViewCustomer Snapshot——Chongqing Shanshui Urban Tourism Development Ltd

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公司规模
200-1,000
地区
  • Asia
国家
  • China
产品
  • QlikView
技术栈
  • Extraction, Tranformation and Loading (ETL) engine
实施规模
  • Enterprise-wide Deployment
影响指标
  • Cost Savings
  • Productivity Improvements
技术
  • 分析与建模 - 数据即服务
适用功能
  • 商业运营
服务
  • 数据科学服务
关于客户
Chongqing Shanshui Urban Tourism Development Ltd is a part of the Chongqing Jiaotong Tourism Investment Group Co., Ltd. The company is mainly involved in investing in tourism projects, development of tourism resources, planning for tourism products and advertising of tourist spots, design, production, agency, hotel management, and management of tourist attractions. Established in 2007 with a registered capital of 165 million yuan.
挑战
Before adopting a BI platform, Chongqing Shanshui was putting together data from a complicated list of sources, including a financial system with ERP functions, as well as disparate Excel files. Report development was rigid and they were not able to maximize the use of existing data. Due to the nature of its industry, Chongqing Shanshui needed to get the latest insights into its business quickly.
解决方案
The first phase was rapidly deployed by Chongqing Shanshui within 1 month. They used QlikView’s Extraction, Tranformation and Loading (ETL) engine to quickly extract and consolidate the disparate Excel data. They developed a unified and centralized decision support platform, ensuring the accuracy and timeliness of the data. This in turn enables the management to make critical decisions impacting the business.
运营影响
  • Regulation of basic data, increasing the data accuracy and effectiveness, ultimately providing management with an objective view of the business to aid decision-making
  • Flexibility to swiftly analyze the huge volume of data typically generate in the tourism industry from any angle
数量效益
  • Rapidly aggregate disparate data, achieving 30% savings in human resources required for data analysis

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