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Private and Open Data in Asia: A Regional Guide.
The huge volume of time series data which is generated across all processes for product is obtained in manufacturing industry. The availability of machine-generated data in IT system enable us to do yield management, fault detection and process control.
However, the growing volume of data with manufacturing facility growth is so fast.
Existing legacy system based on RDBMS had its limitations. A fast-growing volume of data has outstripped the plan of expanding disk capacity. And too many indexes which was used to improve the performance, made the slow down the performance of database. Quite a number of records made speed down data query performance also. To make matters worse, the data compression based on BLOB type for cost saving made the query slow further.
With Big Data system using Hadoop platform, we resolved the problems. And we set up real-time pattern analysis system using Spark. It provides easy and quick solutions to hands-on worker to monitor and diagnose manufacturing processes rather than traditional legacy system based on RDBMS.
This session will address advanced manufacturing solution based on Hadoop platform and its implication.
This session is sponsored by SK telecom
SeongHwa Ahn currently works on various things related to Apache Hadoop at SK Telecom with his primary focus on solving telco and manufacturing industry problem. He has spent 18 years working in IT services and has experience in big data, media mining, cache cloud, portal service, operating manufacturing system, educating. Especially he has worked for 8 years as performance engineer at IT services after 2008.
Ji Sung Kim is a IT manager in SK Telecom which is the largest wireless telecommunications service provider of south korea. He has been working in the area of building big data applications. He participated in developing the weblog analytics in enterprise portal environment and real-time data processing/analytics in manufacturing process etc.
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