Cloud Computing Infrastructure for Massive Data: A Gigantic Task Ahead

Today, in the era of computer we collect and store data from innumerable sources and some of these are Internet transactions, social media, mobile devices and automated sensors. From all of these sources massive or big data is generated and gathered for finding the useful patterns. The amount of data is growing at the enormous rate, the analyst forecast that the expected global big data storage to grow at the rate of 31.87% over the period 2012-2016, thus the storage must be highly scalable as well as flexible so the entire system doesn’t need to be brought down to increase storage. In order to store and access the massive data the storage hardware and network infrastructure is required.

Cloud computing can be viewed as one of the most viable technology for handling the big data and providing the infrastructure as services and these services should be uninterrupted. This computing is one of the cost effective technique for storage and analysis of big data.

Cloud computing and Massive data are the two rapidly evolving technologies in the modern day business applications. Lot of hope and optimism are surrounding around these technologies because analysis of massive or big data provides better insight into the data that may create competitive advantage and generates data related innovations having tremendous potential to revive the business bottom lines. Tradition ICT (information and communication) technology is inadequate and illequipped to handle terabytes or petabytes of data whereas cloud computing promises to hold unlimited, on-demand, elastic computing and data storage resources without huge upfront investments that is otherwise required when setting up traditional data centers. These two technologies are on converging paths and the combinations of the two technologies are proving powerful when it comes to perform analytics. At the same time, cloud computing platforms provide massive scalability, 99.999% reliability, high performance, and specifiable configurability. These capabilities are provided at relatively low cost compared to dedicated infrastructures.

There is an element of over enthusiasm and unrealistic expectations with regard to the use and future of these technologies. This chapter draws attention towards the challenges and risks involved in the use and implementation of these naive technologies. Downtime, data privacy and security, scarcity of big data analysts, validity and accuracy of the emerged data pattern and many more such issues need to be carefully examined before switching from legacy data storage infrastructure to the cloud storage. The chapter elucidates the possible tradeoffs between storing the data using legacy infrastructure and the cloud. It is emphasizes that cautious and selective use of big data and cloud technologies is advisable till these technologies matures.