Current challenges for big data platformsĪs the quantity of data continues to increase and the applications of data diversifies, the technology for big data platforms has also evolved. That’s why we need a powerful big data platform that supports highly efficient data analytics, engineering and governance across different cloud platforms and data processing tools. But using multiple public clouds and open source software inevitably complicates the ways we gather and manage our ever-increasing business data. To easily build a unified user experience across all our different cloud platforms, we rely on different open source tools. As an example, we use Google Cloud, because its infrastructure tools like Google Kubernetes Engine (GKE) and Spot VMs help us further lower our computing costs, while the combination of BigQuery and Firebase for data processing speeds up our data-driven decision-making. SHAREit Group has adopted a multicloud strategy to deploy our products and run data analytics since our early days because we want to avoid provider lock-in, take advantage of the best-of-breed technologies, and avoid potential system failures in the event that one of our multiple cloud providers encounters technical issues. We could never achieve this without the insights we gained from our business data for product improvement and development. Over the past years, our mobile app products, notably the file sharing platform SHAREit, which aims to make content equally accessible by everyone, has quickly gained popularity and reached more than 2.4 billion users around the world. At SHAREit Group, we heavily rely on data analytics to continue optimizing our services and operations. Fully unleashing the power of data is an integral part of many companies’ goals of digitalization.

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