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Xiamen Dianchu Technology is a mobile game developer founded in 2013.It has released and continues to operate many games with historical themes, such as Game of Sultans and Game of Khans. Its games are frequently recommended by Google, and some of them are quite popular in App Store. Game of Sultans, the company's star product, earns more than CNY 100 million for the company every month, with users spanning across the US, the Middle East, and other countries and regions. Dianchu Technology is always developing more games for the international market, and its net profit has seen a 221.15% increase over the last three years.
Xiamen Dianchu Technology is a mobile game developer founded in 2013.It has released and continues to operate many games with historical themes, such as Game of Sultans and Game of Khans. Its games are frequently recommended by Google, and some of them are quite popular in App Store. Game of Sultans, the company's star product, earns more than CNY 100 million for the company every month, with users spanning across Russia, the US, the Middle East, and other countries and regions. Dianchu Technology is always developing more games for the international market, and its net profit has seen a 221.15% increase over the last three years.
Dianchu Technology big data team uses Huawei Cloud intelligent data lake to quickly resolve pain points
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DLI+OBS: DLI provides cross-source query capabilities and enables customers to analyze different data sources without migrating them. It also provides SQL-like serverless services that do not require O&M, enabling customers to stay focused on development. In addition, an architecture with decoupled storage and compute is more cost-effective.
DWS: High-performance query and OLAP analysis meet Dianchu Technology's requirements for real-time data warehouses in the future.
DGC: full-lifecycle data management, job dependencies and lineages, and clear and efficient job management
DLI+OBS: DLI provides cross-source query capabilities and enables customers to analyze different data sources without migrating them. It also provides SQL-like serverless services that do not require O&M, enabling customers to stay focused on development. In addition, an architecture with decoupled storage and compute is more cost-effective.
DWS: High-performance query and OLAP analysis meet Dianchu Technology's requirements for real-time data warehouses in the future.
DGC: full-lifecycle data management, job dependencies and lineages, and clear and efficient job management
Integrated storage and compute do not support evolution
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•The big data platform of Dianchu Technology integrates data from sources such as tracking data of game clients, data collected from server interfaces, and data from app markets and game forums. The data is scattered and not correlated for analysis. There are no precise user profiles, and operational activities cannot target specific users, resulting in a low conversion rate.
•Code is still used for development. There is no unified platform that schedules and governs jobs, resulting in inefficient development.
•With the original big data platform, the storage and compute were tightly coupled and did not support evolution. To scale out storage, compute resources had to be scaled along together. This made storage expensive and flexibility poor. The private services used in HBase were affecting service iteration.
•The big data platform of Dianchu Technology integrates data from sources such as tracking data of game clients, data collected from server interfaces, and data from app markets and game forums. The data is scattered and not correlated for analysis. There are no precise user profiles, and operational activities cannot target specific users, resulting in a low conversion rate.
•Code is still used for development. There is no unified platform that schedules and governs jobs, resulting in inefficient development.
•With the original big data platform, the storage and compute were tightly coupled and did not support evolution. To scale out storage, compute resources had to be scaled along together. This made storage expensive and flexibility poor. The private services used in HBase were affecting service iteration.
•Optimized architecture that supports technology evolution
Huawei Cloud DLI and OBS decouple compute and storage resources, reducing the TCO by 30% and enabling data sharing. DLI is compatible with the Kubernetes and Docker ecosystems and supports user-defined container images, enabling evolution of a container-based architecture and agile iteration.
•Easier big data usage and development
With DLI, Dianchu Technology is able to develop 80% of its jobs faster using standard SQL statements. DGC supports multiple scriptand job versions. DGC improves development efficiency through version management and allows developers to roll back a version if needed, greatly improving the efficiency of collaborative analysis by multiple departments.
•Cross-source analysis facilitates user profiling, precision marketing, and user retention
Data Lake Insight (DLI) provides cross-source federated analysis to break data silos and enable more comprehensive player profiling for better precision marketing and user retention. For example, when players purchase new items for their accounts, that data can be associated with user registration data. The system can then push advertisements to users of a certain age group, improving user retention rate by 20%.
The big data solution of Huawei Cloud has lightened our O&M workload so that our big data team can focus on services, respond quickly to data analysis requirements, and explore the value of data. We look forward to the DLI and DGC services from Huawei Cloud providing our big data team with better insights into game products.
The big data solution of Huawei Cloud has lightened our O&M workload so that our big data team can focus on services, respond quickly to data analysis requirements, and explore the value of data. We look forward to the DLI and DGC services from Huawei Cloud providing our big data team with better insights into game products.