The popularity of Big Data lies within its broad definition of employing high volume, velocity, and variety data sets that are difficult to manage and extract value from. Unsurprisingly, most businesses can identify themselves as facing now or in future Big Data challenges and opportunities. This therefore is not a new issue yet it has a new quality as it has been exacerbated in recent years. Cheaper storage and ubiquitous data collection and availability of third party data outpaced the capabilities of traditional data warehouses and processing solutions. Businesses investigating Big Data regularly recognize that they lack the capacity to process and store it adequately. This manifests either in an incapability to utilise existing big data sets to the fullest or expand their current data strategy with additional data.
Today, as a consequence of the Big Data trend, Businesses can turn to Big Data as a Service (BDaaS) solutions to bridge the storage and processing gap. Interestingly, a definition and classification of BDaaS is missing today and various types of services compete in the space with very different business models and foci. Businesses investigating Big Data and BDaaS, however, would be well served to review the types of services and how they align with their business goals before drilling down and evaluating instances of these services. What are the different types of BDaaS available?
This article discusses the following types of BDaaS: