Test Rigorously and Risk-Free with High-Quality Synthesized Data
公司规模
Large Corporate
产品
- Synthesized DataOps Platform
技术栈
- AI-driven Data Synthesization
- DataOps
实施规模
- Enterprise-wide Deployment
影响指标
- Productivity Improvements
- Customer Satisfaction
- Digital Expertise
技术
- 分析与建模 - 数据即服务
- 分析与建模 - 预测分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- 金融与保险
适用功能
- 商业运营
- 质量保证
服务
- 数据科学服务
- 系统集成
关于客户
The leading credit provider sought to create its own scoring model and firmly believed that it could drive further growth by increasing the accuracy of its customer segmentation. They saw the potential of Synthesized data in facilitating this powerful business transformation. With the Synthesized platform, they obtained immediate access to an unlimited volume of Synthesized data automatically created, compared to roughly ten hours by their closest competitor. The data remained up-to-date, fast, and simple to provision on-demand, with zero risk of exposing any sensitive customer information. They also benefited from comprehensive test coverage, including outliers and edge cases, and 1000+ simulated data scenarios for both functional and non-functional testing purposes.
挑战
Rather than depending on a third party vendor, the customer sought to create its own scoring engine, and was looking for a robust solution that would support them in successfully deploying self-built, proprietary systems. Historically, such ambitions proved impossible to achieve due to the high volume of realistic profiles required. More importantly, the small number of manually-created profiles performed poorly when tested for new segmentation models. To safely deploy the engine, they would need to carry out extremely thorough testing on millions of representative customer profiles. The new engine would need to be properly tested against all possible scenarios, including scenarios that did not exist within the customer data - All that, without putting customer data at risk. Deploying the system without rigorous testing and validation would have resulted in downtime, reputational risk, and the potential for incorrect outputs on a large scale. To overcome such key challenges, the customer partnered with Synthesized, using our ML-driven synthesization engine.
解决方案
The customer was able to rigorously test its segmentation engine before launch, using high-quality, representative data generated by Synthesized, all with zero risk of exposing any sensitive customer information. Using the Synthesized DataOps platform, they were able to achieve reduced time needed to access data, with data automatically created within minutes, versus up to two days through the manual approach. This was faster than any other competitive solution, which took on average around ten hours. The data remained up-to-date, fast, and simple to provision on-demand. They also obtained millions of high-quality datasets, with a large volume of highly representative synthesized data mirroring the qualities and utility of the original dataset. This included comprehensive test coverage, outliers, and edge cases, with 1000+ simulated data scenarios for both functional and non-functional testing purposes. Additionally, the solution reduced organizational complexity by consolidating test data projects into one single platform synchronized with data sources, enhancing collaboration in the cloud among distributed teams.
运营影响
数量效益
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