Big Data Analytics Research Papers - Academia.edu.
External and Internal Data based Business Intelligence Thesis Topics. In order to make complete analysis of the business performance of an organization in the market it is very important to analyze both external and internal data of the company. External data is collected from the market where consumer likes or dislikes the product.
Hi All, I am an MSc Data Analytics student, who is looking for a research project for the final year thesis. I have two ideas in mind, one idea is in line with the prediction of a natural disaster, another one is in line with the e-commerce sector.
The current view of analytics is encapsulated by Davenport and Harris’ (2007) succinct and widely adopted definition: “By analytics we mean the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.” (p. 7, emphasis in the original).
Research Paper Topics By Subject Another way of choosing the best research paper topic is based on the subject, whether you are a college or high school student. Whether it is on biology, physics, science, literature, history, or psychology, this approach works at all levels of education.
While the maximum number of Big Data research papers is in the field of computer science (171), other academic fields for this line of research include Engineering (75), Mathematics (33), and Business Management (26). Listed below are the 5 trending research topics being pursued by PhD scholars around the globe: Big Data analytics.
With the right approach, business intelligence can be a leading source of competitive advantage. Organizations have an opportunity to use enterprise analytics to drive digital transformation and redefine the customer experience. To accomplish this, data and analytics leaders must create a data-driven culture focused on delivering business outcomes.
Data analysis and research in qualitative data work a little differently than the numerical data as the quality data is made up of words, descriptions, images, objects, and sometimes symbols. Getting insight from such complicated information is a complicated process, hence is typically used for exploratory research and data analysis.