The global big data market is mainly driven, by increasing market of consumer, and machine data. The increasing detail and volume of information captured by enterprises, the upsurge of multimedia, social media, and the internet of things, is expected to fuel the growth of the big data market, in the near future. Some of the other drivers fuelling the growth of the big data market, are new applications leveraging big data, and demand of unified platforms.
Big data usually includes large sets of data, with sizes (petabytes and exabytes) beyond the ability of commonly used software tools to acquire, manage, and process data, within the lapsed time. Big data is the high-variety and high-volume information assets that require inventive forms of information processing, for improved understanding, and decision making. Big data is a developing term that defines a huge amount of structured, unstructured and semi-structured data, having the potential for information mining. Though big data does not refer to any explicit quantity, however the term is commonly used, when it comes to processing extensively large quantities of data.
The global big data market can be segmented on the basis of types, services, and end users. On the basis of types, the global big data market can be categorized into software, hardware, and services. The software segment can be further segmented, into discovery and visualization tools, databases, hadoop distribution tools and products, system software, and others.
Demand of advanced analytics and data warehousing, among big data applications and big data security intelligence, are some of the opportunities, for the growth of the global big data market, during the forecast period.
However, lack of security measures, agreement for big data governance, and lack of skilled personnel, to convert machine learning to operational workflows are some of the restraints associated with the global big data market. The major limitation in this market is the lack of skilled personnel. There are large number of data scientists and IT staffs that are aware of the potential of big data; however they are unable to implement them effectively, due to the lack of expertise in this domain.
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