Data Trasfer From MySQL To Hadoop

Pippal, Sanjeev Kumar; Singh, Shiv Pratap; Kushwaha, Dharmender Singh

doi:10.1145/2677855.2677934

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…Numerous popular ETL (Extract, Transform, and Load) solutions are currently available for usage at this step to bulk load data from a range of data sources, including CSV files, NoSQL databases, and relational databases, into a particular database management system. Apache Sqoop is commonly used to export and import huge volumes of data effectively between the Hadoop Distributed File System (HDFS) and structured data storage such as relational databases [39].…”

Section: Etl Toolmentioning

confidence: 99%

From Customer Data to Smart Customer Data: The Smart Data Transformation Process

et al. 2022

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Nowadays, smart data has emerged as a new trend in creating more business value for enterprises that is defined as the data that is gathered and processed to create new insights to support business decisions. However, the transformation from data into actionable insights is still a real challenge for enterprises. For this reason, this paper presents a smart data transformation process, which aims at transforming customer data into smart customer data in order to offer actionable insights. The purpose of the study is to propose a transformation process that can be used to operate a knowledge structure for a smart service system, which can manage and deliver smart data as a service. The process covers the three dimensions of a service system: Data processing corresponding to the engineering dimension, information processing corresponding to the science dimension, and knowledge processing corresponding to the management dimension for knowledge processing. Accordingly, a case study on the smart data transformation process of a customer journey management system as a smart service system is presented to demonstrate the application of the proposed process.

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Section: Etl Toolmentioning

confidence: 99%