The huge amount of data burst which occurred with the arrival of economic access to the internet led to the rise of market of cloud computing which stores this data. And obtaining results from these data led to the growth of the “big data” industry which analyses this humongous amount of data and retrieve conclusion using various algorithms. Hadoop as a big data platform certainly uses map-reduce framework to give an analysis report of big data. The term “big data” can be defined as modern technique to store, capture, and manage data which are in the scale of petabytes or larger sized dataset with high-velocity and various structures. To address this massive growth of data or big data requires a huge computing space to ensure fruitful results through processing of data, and cloud computing is that technology that can perform huge-scale and computation which are very complex in nature. Cloud analytics does enable organizations to perform better business intelligence, data warehouse operation, and online analytical processing (OLAP).
TopIntroduction
The term “Big Data” used for explaining some detailed information of massive volume. Those data can be in both structured and unstructured form. This data can’t be handled using traditional database methodologies and software technologies. The endless growth in volume is due to data which are being captured by organizations, social media sharing, and use of smart products i.e. IoT enabled devices has resulted in a massive data outbreak. The following graphical analysis will give a more clear view of the Big Data market scenario. (Sujitha & Praveen, 2015)
Figure 1. Growth of Big Data Market Value
Here the graphical growth shows how the industry paced over the few years and how it will go for the next 8-10 years.
The following definition of Big Data is proposed on the basis of the 4 V’s namely, Volume, Variety, Velocity and Value. Big Data is a set of techniques and technology that require new forms of integration to uncover large hidden values from large datasets that are diverse, complex, and of massive scale.
Figure 2. Source: Created by author One of the most accepted definition of Cloud Computing is given by NIST it states as –
Cloud Computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resource (e.g. networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.
In general various organizations adopt 3 (three) types of cloud deployment models namely Private Cloud, Public Cloud, Hybrid Cloud. (Deshmukh & Sumeet, 2015)
Cloud computing is a low cost, economical model that’s being used for big data analytics. The convergence of Big Data and Cloud technology make big data analytics more successful outcomes. Various organizations moved towards dedicated servers for getting better analytical result. Hadoop can certainly deliver more accurate and critical results beyond some of the web scale companies such as Yahoo, Spotify. (Khan et al., 2013)
The Cloud computing delivers various service models to its user as service-based services in pay you go form. It delivers infrastructure, platform, and software as services. These services are namely, Infrastructure as a Service (IaaS), Platform as a Service (Paas), and Software as a Service (Saas). [4]
Traditional computing methods are getting out of the plate as the rate of growth of data is too high and with the passing of each day the data is becoming complex in nature, which triggered the big data application. Huge amount of intermediate data is being produced by these defacto softwares namely Google’s map reduce framework and apache Hadoop. (Mayilvaganan & Sabitha, 2013)
With the rapid increase of Internet of Thing (IoT) and future internet the concept of smart city evolved in a pretty rapid pace. There is a generation of huge amount of data this data needs to be properly managed and analyzed using integrated Information Communication Technology (ICT) approach. With the arrival of ICT it brings some significant changes smart cities governance. Processing and integration of cross-disciplinary data is the key for knowledge and intelligence for sustainability, resilience of the governance of the city. (Ramamoorthy & Rajalakshmi, 2013)