Computational Techniques in Data Integration and Big Data Handling in Omics

Veras, Adonney Allan de Oliveira; Sá, Pablo Henrique Caracciolo Gomes de; Pinheiro, Kenny da Costa; Barh, Debmalya; Azevedo, Vasco; Ramos, Rommel Thiago Jucá; Silva, Artur da Costa da L.

doi:10.1016/b978-0-12-804659-3.00012-9

Cited by 1 publication

(2 citation statements)

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“…MapReduce is a technique designed by Google which has the ability to control large amount of data using a cluster system. Hadoop is another framework created from MapReduce and Big-Table for the purpose of allowing parallel processing in groups of high latency and this system has tolerance requirement s for any failure and load assessment [12].…”

Section: Big Datamentioning

confidence: 99%

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A Theoritical Exploration of Data Management and Integration in Organisation Sectors

Offia¹,

Crowe²

2019

IJDMS

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Big data development is a disturbing issue that will affect enterprise across various sectors. The increase of data volume, high speed of data generation and increasing rate of different data from heterogeneous sources have led to difficulties in data management. This paper first reviews different aspects of big data management, including data integration and traditional data warehouse, and their associated challenges. The problems include increase of redundant data, data accessibility, time consumption in data modelling and data movement from heterogeneous sources into a central database, especially in the big data environment. We then propose a logical data management approach using RESTview technology to integrate and analyse data, without fully adopting traditional ETL processes. Data that for governance, corporate, security or other restriction reasons cannot be copied or moved, can easily be accessed, integrated and analysed, without creating a central repository. Data can be kept in its original form and location, eliminating the movement of data, significantly speeding up the process and allowing for live data interrogation. It may not be the practical solution for every situation but, it is a feasible solution that is comparably cost effective.

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Section: Big Datamentioning

confidence: 99%

“…Data from mobile apps like google map for transportation generate floods of information that can be utilized through producing real-time data and also the pattern and behaviour of data can be observed [11]. Cloud computing was designed with the promise to solve the data storage and its processing time challenges [12].…”

Section: Big Datamentioning

confidence: 99%

A Theoritical Exploration of Data Management and Integration in Organisation Sectors

Offia¹,

Crowe²

2019

IJDMS

View full text Add to dashboard Cite

show abstract

Computational Techniques in Data Integration and Big Data Handling in Omics

Cited by 1 publication

References 61 publications

A Theoritical Exploration of Data Management and Integration in Organisation Sectors

A Theoritical Exploration of Data Management and Integration in Organisation Sectors

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