Big Data Analytics
After reading this paper, you should clearly understand the relationship between the analytic methodologies and techniques associated with big data and how to integrate it with a new correlation taxonomy. This paper adds more distinction to the 5Vs of big data you read about previously. You will recognize the characteristics and significance of the descriptive, diagnostic, predictive, and prescriptive integration methods.
6. Conclusions
The development of the big data analytics correlation taxonomy for identifying BDA methods and its associated techniques based on research approach methods was achieved through the cross-fertilisation of two stages to understand the correlation between the analytical methods and the correlation of the analytical methods and its associated techniques. These were deemed relevant and helpful in addressing the lack of guidelines for researchers to understand the correlation between big data analytic methods and its associated techniques. Therefore, the main contribution and novelty of this paper is our proposal of a big data analytics taxonomy techniques according to a research approach and big data analytics methods.
This paper has reviewed and reflected big data analytics and presented the current interest in this field. It has defined what was meant by big data, then highlighted the fact that big data analytics has many characteristics and it is worth mentioning that the correlation taxonomy proposed in this paper is not affected by a number of the big data analytics characteristics and should be applicable for any number of Vs'. Furthermore, the paper has investigated the most popular sectors where big data analytics made an impact. After defining the existing analytical methods, this paper made the case for a new analytical methods category and how they complement each other. Design science research has been adopted and five DSRM elements were chosen to accomplish the project, which helped in developing the concept successfully.
Finally, the work presented here is ongoing. The following phases of the research will be to: (1) continue the investigation on the validity of big data analytics characteristics used in industry; (2) continually test and assess the proposed taxonomy in a specific sector; (3) identify and highlight the positive and negative implication examples; and (4) specify the limitations and the difficulties raised; and (5) update the taxonomy based on the outcomes from the previous points.