Support automation connectivity system for big data applications

Abstract

The business information is stored in different source systems. Accessing specific data from different source systems that contain terabytes of information is tedious. The organization's source systems are complex and hence data extraction could be time consuming and labor-intensive. Not all users are allowed to access the production data due to security limitations and performance issues. Business leads will not be able to make the right decisions if the available raw data is not presented in the right context and the performance cannot be monitored. There is a need to automate the data extraction process targeting the different data sources and the need of Business Intelligence to gather and analyze data, transform it to useful form to gain insight to make decisions. The paper proposes, Support Automation Connectivity approach which addresses these issues using SNPN (Serial and Product Number) Data Extraction system and Store Serve Reporting. Support Automation Connectivity is about tracking the information of the connected Enterprise devices. The intelligent software built into the products sends heartbeat at regular intervals. This helps in supporting the device in terms of failures or software version updates, etc. based on the warranty period. The data is maintained in different cubes. SNPN Data Extraction system allows the business user to analyze the attributes related to connected devices for the given SNPN and report date. This system is triggered by the scheduler at regular intervals to pick up the input files for processing. It performs the data extraction within few seconds even for large data and sends instant notification to the relevant individuals. The file and package execution details can be tracked and appropriate error handling is implemented.