Big data infrastructure and methodology continue to evolve at an exponential pace, but the underlying technologies were, in many cases, invented many years ago. In an effort to help IT decision makers make better, more informed choices associated with these technologies, the Cloud Security Alliance (CSA) has released the Big Data Taxonomy Report, a guidance report that aims to help navigate the myriad choices within the big data designation.
Every day, a mind-boggling 2.5 quintillion bytes of data are created—and in fact, 90% of the data in the world today has been created in the last two years alone. That leads to issues of storage, computer horsepower, security, privacy and analytics, because these are all magnified by the velocity, volume and variety of big data, such as large-scale cloud infrastructures, diversity of data sources and formats, streaming nature of data acquisition and high volume inter-cloud migration.
“The greatly increased digitization of human activity and machine-to-machine communications, combined with large-scale, inexpensive hardware, is making practical many previously academic ideas of parallel and distributed computing, along with new considerations necessary to make them even more useful in real-world applications,” said Sreeranga Rajan, chair of the CSA’s Big Data Working Group, in a statement.
The CSA Big Data Working Group’s 40-page guidance report outlines the six dimensions: data domains, computer infrastructure, storage infrastructure, analytics, visualization, security and privacy. Each domain is categorized according to how data arises, to help decision makers understand the infrastructure choices and requirements for particular types of data. The report also addresses each particular domain in which data arises, to help organizations determine the types of architecture that will be required to store it, process it and perform analytics on it.
“All ‘data’ is not equivalent, yet we often find users treating all data components similarly, as they are uncertain as to how to address issues such as latency, or structured versus unstructured data,” said Rajan. “We hope this report brings clarity to the big data taxonomy, and provides much needed education to help users make better decisions in their own environments.”