Big Data Analytics Platform
Industry Problems
Smart City in the big data challenge from Smart City itself. Therefore more need to build a complete information system to solve a steady stream of data generated, a steady stream of data input data, the system is more to the system inside the huge, then the data collected by how rational analysis and processing, and found valuable information to the city of impending problems proactively forecast and a more rational allocation of resources to improve the operational efficiency of the city has become a top priority issue.
Solution Overview
CertusNet integrated data analysis platform for big data analysis as the core, using Hadoop and Storm two kinds of big data analysis engine, both to ensure that the vast amounts of data analysis, but also to ensure that the data analysis and mining real-time. On industry applications, big data analytics platform for big data analysis to meet government requirements, but also for providing data mining, data analysis services.
•     High reliability: by the ability to store and process data bit worthy of the trust.
•     Highly scalable: allocation of available computer data between clusters and complete computing tasks, these clusters can be easily extended to thousands of nodes.
•     Efficiency: the ability to dynamically move data between nodes, and each node to ensure homeostasis, so the processing speed is very fast.
•     High fault tolerance: the ability to automatically save multiple copies of the data, and can automatically reassign tasks will fail.
Key Technologies
•     Massive data analysis
•     Hadoop data analysis engine with the Storm
•     Data mining, data analysis techniques
•     Smart City Comprehensive Data Analysis Platform can design data resource planning; establish a sound data updates, maintenance, service mechanism. Provide timely, accurate and effective data support an important guarantee for the integrated management of the daily.
•     To provide support for the IT infrastructure and resources to provide standardized data collection, processing, integration, presentation and service.
•     Through current or historical data in the data warehouse a lot of different data sources were integrated, summarize and generalize, to build the index system of urban operations, strategic decision analysis applications, support management, production and operational decisions.