Based on your understanding about big data, some supportive material, and guest lectures, please come up your own ideas about big data. Three-to-four pages are sufficient. Four-page will be maximum. Please do NOT go beyond four pages.
Title
Abstract
The abstract is usually a short paragraph in which the paper content is concisely introduced. The abstract is expected to be shorter than 200 words. You should highlight your problem and results in the abstract.
Introduction
The topic background is usually reviewed and expanded in the introduction section. The problem you are looking for solutions should be described. Some overlap with abstract is acceptable.
You may discriminate and distinguish the concepts and phrases that appear in the paper for several times, or that may confuse your readers so that your readers could carry on reading the following sections.
Taking "big data" as an example, you may thoroughly interpret and compare "big data," "data analysis," "analytic," and "data-driven." You can choose the following structure of the main content that is described in the following sections. However, you can also be creative in creating your presentation style.
Literature /Progress Review
The related literature should be summarized in this section and, of course, thoroughly read before you start the paper. By doing this, you could figure out and tell your readers what your main content is.
Some latest important progress in the industry may also be mentioned. For example, big data techniques are useful in promoting efficiency, reducing costs and increasing convenience for those internet companies. If you are not doing an empirical study, you should put more effort in this section.
Methodology and Data
The logic, experiment design and techniques you employ to proceed in your study need to be discussed in this section. Your data, their source, and the processing need to be specified so that your readers could duplicate the outcome of your paper.
If you are not doing an empirical study, you could review the existing commonly used big data techniques, describe some typical data structures and introduce how data scientists manipulate or process data.
Results
You may provide your readers with the results you attain during study or literature surveys through experimental research or paper review. Highlight them if your results are consistent with or conflicting to former studies.
By comparing several existing data transformation techniques and your proposed method in this paper, you can derive the conclusion that your model is better or worse than other solutions.
Implementation and Application
You need to specify your findings if the findings are useful in daily life or industry. If you are writing a white paper and will not undertake experimental studies, you may discuss several cases that existing techniques could be applied in daily life or industry.
Conclusions and Discussions
This is the section where the paper concludes. You may go through the main steps in your study. The conclusions are supposed to be highlighted here. You may also discuss the weakness in your research, potential solutions, and possible future endeavors. As for an essay on the topic of "big data," you can also mention some challenges in this field or some controversial issues. The conclusion part consists of one or two short paragraphs.