Big Data Modelling: Proposed Feature-Based Modelling Technique

BIG DATA MODELLING, PROJECT PROPOSAL 1
BIG DATA MODELLING, PROJECT PROPOSAL
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BIG DATA MODELLING, PROJECT PROPOSAL 2
Table of Contents
1.0 Introduction................................................................................................................................3
2.0 Research background.................................................................................................................3
3.0 Research problems.....................................................................................................................4
4.0 Research objectives...................................................................................................................5
5.0 Proposed modelling technique...................................................................................................5
6.0 Conclusion.................................................................................................................................7
7.0 References..................................................................................................................................7

BIG DATA MODELLING, PROJECT PROPOSAL 3
1.0 Introduction
Just like the case for other real-life applications in the library where books need to be
classified and arranged systematically on shelves so that they can be accessed easily, the massive
data handled in big data applications need an effective way to be kept in order. This process of
sorting and storing big data is called “data modelling”. In its basic definition, a data model is a
method used to organize and store data just like it is the case with the Dewey Decimal System
when it comes to organizing books in a library. Effective Data modelling in big data applications
will help arrange data in accordance with its services and usage (De Martino et al, 2014, p.650).
Through that, improved performance can be realized in big data applications considering the fact
that data models will optimize the speed of querying and reduce the input-output throughput. The
cost of handling big data will also be minimized in consideration to the fact that effective data
models will significantly reduce data redundancy. Lastly, effective data modelling approaches
will improve the quality of big data application outputs through consistent statistics and reduced
computing errors (LaValle et al, 2011, p.21).
2.0 Research background
The expansive growth in internet usage capacity, smart devices and all the other forms of
information technology in the current digital era has led to an equally impressive data growth
rate. The trend has appeared with its own challenges considering the fact that traditional
approaches to data classification, organization and storage had been designed to accommodate
small amounts of data (Lee, 2005, p.950). For instance, statistics have shown that the huge
amounts of data handled by the data stream applications cannot be stored and fully managed in a
system and that raises the concern on looking for better ways to handle data in such an
application. Additionally, contrary to traditional data, the arrival rate of the data stream has been