Sustainability and conservation of energy resource in a developing country such as Bangladesh is a major concern for the people and their government. Massive amount of data is being generated in the energy sector which is untapped and can potentially provide a roadmap to ensure the sustainability of energy resources. We present an approach on how big data can help us find meaning in the data that is available and how analyzing the data can help countries like Bangladesh to set aside and distribute energy in an efficient manner while also providing environmental benefits. We classified the data sources and presented a high-level design that would help us implement such a solution in future. Finally, we discussed the applications of the analysis and how we can move forward towards additional points of interests for achieving energy sustainability.

The importance of software quality assurance is often overlooked in startups, leading to consequences that deem the product and subsequently the startup to fail in the long run. This paper looks into the current software quality related scenarios present in startups and tries to pinpoint issues which eventually cause their downfall. By acquiring their insight, we hypothesized an adoptable guideline to mitigate the issues faced in the startups and implement a quality framework for any software-based startup organization.