Wefi
公司规模
Large Corporate
产品
- Sisense
- Sisense ElastiCube
技术栈
- SQL
- Sisense ElastiCube
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
技术
- 分析与建模 - 大数据分析
- 分析与建模 - 预测分析
- 应用基础设施与中间件 - 数据可视化
适用行业
- 电信
- Software
适用功能
- 商业运营
- 质量保证
服务
- 系统集成
- 软件设计与工程服务
关于客户
WeFi provides technology for optimizing and managing Wi-Fi networks. For mobile operators, WeFi acts as a data offloading tool in overloaded cellular networks. For end users, WeFi makes it easier for them to find and enjoy optimal wireless connections around the world. WeFi’s tools allow its user community to map the global Wi-Fi network with minimal effort, as over 75,000,000 access points have been identified around the world. Millions of WeFi users are generating seriously big data, and the database team deals with an average table size of more than 5 million rows for behavioral data, and over 500 million rows for activity records of some of the most active clients. Reporting on this activity is essential to helping the company’s management team make decisions.
挑战
WeFi’s database team had been manually running SQL queries, but they struggled to generate the reports that gave the management team crucial feedback. WeFi needed to perform advanced analysis on large amounts of data in three categories: the behavior of millions of WeFi users, including retention activity and data acquisition activity; the performance and activity of wireless networks to which its users are connected; and the activity records of active clients. The average table sizes for these categories were more than 5 million rows, 70 million rows, and 500 million rows respectively.
解决方案
WeFi carried out its initial Sisense implementation by loading data as-is into a single Sisense ElastiCube, and additional stores were added to the server later on. A dedicated PC machine serves as the ElastiCube server, and today the WeFi team runs the majority of its business reporting and dashboards on Sisense, using a total of six ElastiCube data stores. Business users today have the autonomy to create custom dashboards and reports, which dramatically reduces the time it takes to get new data insights; lightning-fast query response times mean answers to key strategic questions are available faster. Meanwhile, the database team can focus on crucial tasks without spending hours writing and running SQL queries.
运营影响
数量效益
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