Big data is used for describing a huge volume of data that includes both structured as well as unstructured data used for inundating businesses on a day-to-day basis. This data is quite huge and is used by organizations for various analysis. Big data and related data sets is so large and complex that the traditional data processing application software is inadequate to deal with them. This includes various data analytics methods such as predictive analytics or user behavior analytics along with other advanced analytics methods used for extracting value from data dealing with a particular size of data set. Big data is analyzed for insights leading to better decisions as well as strategic business moves.
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Big data uses various analytical tools for examining large and varied data sets for uncovering hidden patterns, market trends, unknown correlations and customer preferences among other useful information further helping organizations as a whole in critical decision making process. Various data tools are made for analyzing big data that is mostly used by large multinational companies. But with steady growth of small & medium enterprises, the huge amount of data being generated here has resulted in the application of big data analytics for these enterprises.
The global market for SME big data has been segmented into data type, application and geography. Based on data type, the global market has been segmented into internal data, unstructured external data and structured external data. In addition to this, the various application areas that are considered here includes banking, hypermarkets, travel agents, real estate, IT firms and insurance companies among others.
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Big data analytics helps in monitoring and analyzing the root causes of failures and defects in near-real time thus forming a major driver for this market. The power to help in recalculating the entire risk portfolios within minutes provides support to organizations that are growing further having a positive effect over this market. These analysis also helps in detecting fraudulent behavior within organization before it gets affected along with saving cost and time. These optimizing offerings by new product development thereby assisting in smart decision making.
Along with these drivers, one major restraint that negatively affects the market would be the quality given the huge volume and variety of data available that further creates problem in distinguishing the relevant data from the irrelevant ones.
Moreover, databases may contain all sorts of errors that needs to be rectified for meeting the requisite standards along with problems related to the processing and protection of data that has acted as some major restraints for this market. Given the growth of companies there is likely to be more data that has is expected to provide more opportunities for this market.