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Application Performance Monitoring Leader Increases NRR with Sigma
技术
- 分析与建模 - 预测分析
- 分析与建模 - 实时分析
- 平台即服务 (PaaS) - 数据管理平台
适用行业
- Professional Service
- Software
适用功能
- 商业运营
- 销售与市场营销
服务
- 数据科学服务
- 系统集成
挑战
The Business Intelligence (BI) team faced several challenges due to the increasing demand for data. Fulfilling requests from business teams took up 20% or more of the BI team’s time each week. The complexity of PowerBI made it difficult for business teams, such as Finance and SalesOps, to use, leading to issues like security, governance, and compliance concerns due to data extracts, data sprawl, and outdated data. The BI team was unable to focus on strategic data initiatives and projects. The Finance team struggled to accurately understand customer behavior, product telemetry, and renewal rates, which hindered their ability to forecast revenue accurately. Similarly, the SalesOps team lacked a holistic view of the opportunity pipeline, customer-level pricing, and the impact of different discount rates on revenue, making it challenging to develop effective pricing strategies.
关于客户
The customer is a leader in cloud application performance monitoring (APM) that assists thousands of enterprises globally in automating cloud operations and delivering superior digital experiences to their customers. The company generates a significant amount of data, including millions of rows of product, usage, and customer data. The Business Intelligence (BI) team within the company is responsible for strategic data initiatives, enterprise reporting, and supporting various business teams by answering data-related questions, running ad hoc reports, or providing data extracts. The demand for data was increasing, and the BI team was spending a substantial amount of time fulfilling requests from business teams, which impacted their ability to focus on strategic projects.
解决方案
With the implementation of Sigma, the BI team can now create scalable, reusable data products for the Finance and SalesOps teams. This allows these teams to securely conduct cohort analysis, forecasting, scenario modeling, and more independently. Sigma was designed specifically for the cloud, providing the Finance and SalesOps teams with direct access to live data in PostgreSQL. This ensures that everyone works with the same current data, eliminating issues like stale extracts, data sprawl, and conflicting insights. Sigma’s cloud-native nature delivers unlimited scale and speed, enabling business users to analyze and filter billions of rows of product and customer data without latency delays. The user interface of Sigma makes iterative ad hoc analysis accessible to anyone, allowing business users to slice and dice data, build pivot tables, and create complex calculations on the fly. This capability enables them to accurately assess the pipeline, forecast, identify new opportunities, and set pricing to optimize revenue.
运营影响
数量效益
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