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Data Processing Architecture using Opensource Bigdata Technology to Increase Transaction Speed

机译:使用开源大数据技术提高交易速度的数据处理架构

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Data is the sources of decision making in any businesses, whether they are in a big or small operation. Data can provide insights that can help to answer the key business questions through dashboard, and dashboard leads to insights. In this research is conducted to solve the problem about Decision Support System in telecommunication company. Business owners and managers can turn those insights into decisions and actions that improve the business. To turn the data into a dashboard, the data should follow several steps. This process could take a long time for a huge amount of data. The time required for data processing from raw until transform into aggregated value need more than 2 hours. Thus, could hold up decision making process. Therefore, it is needed to develop a good data processing architecture to process the huge data, to make the data processing faster. In this research, data aggregation is processed using Apache Spark. Afterwards, Apache Zeppelin is used to display the information of telecommunication data. This technology is fast enough to process a lot of data in a short time. The result show that the data processing could be shown in the dashboard in a short time and could help the decision making faster.
机译:无论是大型企业还是小型企业,数据都是任何企业决策的源泉。数据可以提供见解,可以帮助您通过仪表板回答关键的业务问题,并且仪表板可以带来见解。为了解决电信公司决策支持系统中存在的问题,本文进行了研究。企业所有者和经理可以将这些见解转化为可以改善业务的决策和行动。要将数据转换为仪表板,数据应遵循几个步骤。此过程可能需要很长时间才能处理大量数据。从原始数据到转换成汇总值所需的数据处理时间超过2小时。因此,可以阻止决策过程。因此,需要开发一种良好的数据处理架构来处理海量数据,以使数据处理更快。在这项研究中,数据聚合是使用Apache Spark处理的。之后,使用Apache Zeppelin来显示电信数据的信息。这项技术足够快,可以在短时间内处理大量数据。结果表明,数据处理可以在短时间内显示在仪表板上,有助于更快地做出决策。

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