Introduction Big Data has been a prominent technological development for quite some years now and one of the main uses of Big Data has been gained by various businesses that have been able to get access to important information and databases. With the increase in the number of e-commerce companies worldwide, large amounts of data get stored in the form of big data. Big Data is extremely important to identify and understand several trends and patterns in customer behaviour(Russom, 2013). Being an emerging trend, and an ongoing topic of interest among tech savvy people, exploring this topic was of great interest for me. While people usually research the impacts of big data, I wanted to focus more on the design and development aspects that relate to the technical expertise that is required for creating and utilizing bigdata databases. There however are several challenges that are faced by companies that opt for Big Data and these challenges can be largely classified into three major parameters which are: volume of data stored, the speed with which data is processed, and accuracy of the data that is processes and retrieved through Big Data related applications. Research Questions What are the challenges faced in the various platforms of Big Data Applications and how can they be overcome? • What are the main challenges that are encountered in Big Data Applications? • What are the impacts of these challenges on the overall performance of Big Data and its applications? • What are possible solutions for overcoming the challenges of Big Data and its applications? Research Methods and Rationale The research design that would be utilized in this part of the research would be qualitative in nature. The research would be comparative in terms of differentiating between the performance of different big data applications on different platforms. There are two ways in which this would be done. One aspect would be to study the applications on different platforms and draw comparison on the basis of the established parameters, and the second aspect is in terms of the literature and reports related to the performance of various platforms. For a comparative study between common concepts in two situations, deploying a qualitative analysis would be required which would seek to explore the specific aspects such as reasons, impacts and factual information related to the subject(Kothari, 2004). By utilizing this research method, the researcher would be able to define the specific problem that is faced in the area of research and through further data collection would be able to point out specific solutions to these challenges. Since the research seeks to understand definite factual information on the subject based on previous information and data that is already available, there is an increased probability of a higher rate of credibility as well as validity in the research. Related Literature and Overview While the use of Big Data in various parts of the world is steadily increasing, there is a definite need to address the challenges and drawbacks that are faced in the process of designing and developing Big Data and related applications. Big Data Analytics and related applications take a significant place for many companies that need specific domain related information and data to function. While this poses significant challenges in terms of cybersecurity and fraud detection, one significant aspect that would need to be considered would be the protocols that would need to be defined while mining large proportions of data(Najafabadi, Villanustre, & Khoshgoftaar, 2015). Challenges here could include choosing the appropriate software and making sure that the data can be protected. Another major challenge, one which would significantly affect the output would be the presence of infrastructure which include adequacy of coolants and location specific requirements that would affect the effectiveness of storing large amounts of data as well as developing big data and related applications(Ali, Qadir, & Rasool, 2016). References Ali, A., Qadir, J., & Rasool, R. (2016). Big data for development: applications and techniques. Big Data Analytics, 1(2). Kothari, C. R. (2004). Research Methodology: Methods and Techniques. New Delhi: New Age International Publishers. Najafabadi, M., Villanustre, F., & Khoshgoftaar, T. (2015). Deep learning applications and challenges in big data analytics. Journal of Big Data, 2(1). Russom, P. (2013). Managing Big Data. TDWI Research.