OPTILYZER: Hawk-Eye Technology for Data Integration & Performance Optimization
Data Comparison and Performance Optimization are key challenges we face when we talk about humongous volume of data. OPTILYZER, a user-friendly interface is proposed to overcome these challenges. The 4V's which are ruling in market due to which Big Data has come into existence that are Volume,...
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| Vydáno v: | 2020 IEEE International Conference for Innovation in Technology (INOCON) s. 1 - 5 |
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IEEE
06.11.2020
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| Abstract | Data Comparison and Performance Optimization are key challenges we face when we talk about humongous volume of data. OPTILYZER, a user-friendly interface is proposed to overcome these challenges. The 4V's which are ruling in market due to which Big Data has come into existence that are Volume, Velocity, Variety and Veracity. Data Analysts use data for activities like forecasting or deep learning and in order to process these data various tools are available which helps to achieve this task with minimum efforts, but problem arises with legacy data. Legacy data piles up the space and hinders the performance of the current process. This system provides an efficient way to archive these data so as to reduce the space and time complexity of the current process also helps to resolve the challenges faced in data comparison between various heterogeneous platforms like Hive, MySQL and Redshift which have different structure and syntax for processing the data. |
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| AbstractList | Data Comparison and Performance Optimization are key challenges we face when we talk about humongous volume of data. OPTILYZER, a user-friendly interface is proposed to overcome these challenges. The 4V's which are ruling in market due to which Big Data has come into existence that are Volume, Velocity, Variety and Veracity. Data Analysts use data for activities like forecasting or deep learning and in order to process these data various tools are available which helps to achieve this task with minimum efforts, but problem arises with legacy data. Legacy data piles up the space and hinders the performance of the current process. This system provides an efficient way to archive these data so as to reduce the space and time complexity of the current process also helps to resolve the challenges faced in data comparison between various heterogeneous platforms like Hive, MySQL and Redshift which have different structure and syntax for processing the data. |
| Author | Rathod, Pawan Manoj Sengar, Rashi Singh Kushwaha, Vartika Alexander, Rhea |
| Author_xml | – sequence: 1 givenname: Pawan Manoj surname: Rathod fullname: Rathod, Pawan Manoj email: var95kush@gmail.com organization: St. Francis Institue of Technology,Computers Department,Mumbai,India – sequence: 2 givenname: Vartika surname: Kushwaha fullname: Kushwaha, Vartika email: pawanrathod519@gmail.com organization: Data Analyst, Technoboltz,Mumbai,India – sequence: 3 givenname: Rashi Singh surname: Sengar fullname: Sengar, Rashi Singh email: rashisingh41@gmail.com organization: Data Analyst, Technoboltz,Mumbai,India – sequence: 4 givenname: Rhea surname: Alexander fullname: Alexander, Rhea email: rhealexx1993@gmail.com organization: Data Analyst, Technoboltz,Mumbai,India |
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| Snippet | Data Comparison and Performance Optimization are key challenges we face when we talk about humongous volume of data. OPTILYZER, a user-friendly interface is... |
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| SubjectTerms | Amazon Web Service (AWS) Business Data integration Distributed databases Hadoop Distributed File System (HDFS) Java Database Connectivity (JDBC) OPTILYZER Optimization Query processing XML |
| Title | OPTILYZER: Hawk-Eye Technology for Data Integration & Performance Optimization |
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