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The company's original IT architecture was deployed locally on-premises, due to which a large amount of data had to be stored locally every day, and some valuable data had to be discarded. With a change in its development direction, the release of new energy vehicles, and the more data being collected, the company needed to upgrade its local on-premise IT architecture quickly to achieve long-term development.
The Data Lake is core to the company's new data ecosystem, collecting data from all channels and ensuring that the data can be applied. Kyligence Cloud provides safe and reliable cloud data management and analytics services: the reliability and security of the cloud platform itself effectively secure the infrastructure; Kyligence Cloud protects data by adopting industry-standard security strategies for data exchange, storage, and access.
Many applications have been trying to leverage the data lake since its launch. The application scenarios of data analytics on the Internet of Vehicles are shown below:
The first scenario is the collection of car owner data. Car owners can access data via mobile apps or in-vehicle applications. Based on the collected behaviors, car owners are classified into groups to achieve precision service marketing.
The second scenario is services-related. The analysis of the churn rate helps to identify which steps caused the churn of car owners during their data access process, so as to optimize the access process and reduce the churn rate.
The third scenario is the collection of vehicle trajectory data. This can result in some derivative services, such as designated driving and more data dimensions.
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