Grab 的数据网格实践（第一部分）：通过认证建立信任

At Grab, our journey towards a more robust and scalable data ecosystem has been a continuous evolution.

在 Grab，我们迈向更稳健、可扩展数据生态系统的旅程一直在持续演进。

Considering the size of our data lake and complexity of our ecosystem, with businesses spanning across ride hailing, food delivery, and financial services, we have been long past the point where a single centrally managed data warehouse could serve all these data needs. Over its first decade, Grab experienced dramatic growth. Like most growing businesses, teams in Grab prioritised delivering new features to meet the demands of their users. This meant that the task of data maintenance had to take a back seat so that development and stabilisation works can be focused to keep up with the growth. However, to prepare Grab for the next 10 years, especially for a future where AI is likely to play an important role, our leadership understood the need for high quality data foundation and gave a mandate to our data teams to uplevel our entire enterprise data ecosystem.

考虑到我们的数据湖规模以及生态系统的复杂性——业务横跨网约车、外卖配送和金融服务——我们早已过了单一集中式数据仓库就能满足所有数据需求的阶段。在成立后的第一个十年里，Grab经历了爆发式增长。与大多数成长型企业一样，Grab各团队优先推出新功能以满足用户需求。这意味着数据维护工作不得不让位于开发和稳定性建设，以跟上增长步伐。然而，为了让Grab为下一个十年做好准备，尤其是在AI可能扮演重要角色的未来，我们的领导层意识到需要高质量的数据基础，并向数据团队下达了全面升级整个企业数据生态系统的指令。

Acknowledging the rising need for data-driven insights and the continuous expansion of our data repository, we initiated our data mesh journey, named the Signals Marketplace, in 2024.

鉴于对数据驱动洞察的需求日益增长，以及我们的数据仓库持续扩张，我们于 2024 年启动了名为 Signals Marketplace 的数据网格之旅。

However, this journey was far from simple. We encountered several critical challenges that required a significant transformation in our approach to data management. Some of the challenges encountered include:

然而，这段旅程远非一帆风顺。我们遇到了若干关键挑战，迫使我们彻底改变数据管理方法。其中一些挑战包括：

• High volume and variety of data being generated: Grab’s diverse operations created both opportunities and complexities. Effectively harnessing this wealth of information required a scalable, streamlined and accessible approach.

  数据体量大且类型多样：Grab多元的业务既带来了机遇，也带来了复杂性。要有效...