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            Smart Big Data Platform(Pandora)

            Pandora is the Smart Big Data Platform for the Qiniu Cloud, providing a simple, efficient and open one-stop big data service.

            Solution Architecture

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            Why Pandora

            Simplicity

            Simplicity

            People can use it without any big data technology background because of its out-of-the-box feature.

            It is quite easy to use with visualized charts showing analysis results.

            High-efficiency

            High-efficiency

            It's easy to deal with massive data processing with high quality and low cost.

            Users can focus resources on business value enhancement.

            There is no need to focus on complex big data implementations.

            Openness

            Openness

            It supports multiple data sources access, perfectly combined with Qiniu's product chain.

            It is highly customizable and can support privatization deployments.

            Empower users with the core capabilities of big data.

            Core Services and Functions

            Workflow

            Visible big data access, transform, export engine help to achieve massive data processing. Topology management of data flows make the data flow modeling convenient and fast for users and give users intuitive grasp of business data flow.

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            LogDB

            Provide log-type data storage and retrieval services. Users can quickly achieve customized word segmentation, data storage, data retrieval and data analysis without any development. Massive amounts of data can be indexed and searched, then operational and maintenance efficiency is improved. And problems can be found and located quickly.

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            TSDB

            A high-performance database that stores time series data is developed specifically for handling high-write and high-concurrent queries. It supports functional computation and group and aggregation of times series data.

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            XSpark

            Spark services are developed based on container technologies. It supports fast one-click cluster deployment with performance of flexible scalability of computing resources,on-demand charges,providing users with fast-food style big data spending power.

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            Typical Application Scenarios

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            Dataized Maintenance

            Unified log management and real-time monitoring of business quality provide more comprehensive data support for daily diagnostic and tune and security issues tracking of users'systems, which enables technicians to search logs with high efficiency in real time and thus quickly locate information, identify root causes of the problems and finally inmprove operational and maintenance efficiency.

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            Dataized Operation

            Users can use big data workflow engine to quickly set up business data flow, gain real-time access to business operation status and conduct multi-dimensional statistics as well as data mining calculations at any time. Due to the shielding of complex big data technology, the business sector no longer have to wait for the development department to respond to data requests. They can easily get data analysis results by simply customizing the flexible configuration and keep abreast of user behavior, drive product optimization iteration and improve operational effectiveness .

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            DEM

            Real-time monitoring and analysis and alarm optimization of critical business systems can be achieved through real-time acquisition of various performance indicators of platforms (e.g. the rate of opening the first screen in seconds, users'terminal fluency and the distribution of users'hotspots).Continuously improving business reliability and stability of platforms,providing excellent experience for the end user .

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            Recommendation System

            The user's profile is mined by analyzing the user's behavior data based on the leading-edge big data algorithm to update personalized strategy in real time. Effectively improving the retention rate, pay rate, active level and other key business indicators.

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            Growth Hacking

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            澳洲幸运5开奖记录
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