Big Data Analytics: The Underlying Technologies Used by Organizations for Value Generation
The expansion of Internet and its applications globally has witnessed generation of high volume of data resulting in high volume of information. In the contemporary era of digital world, data is seen as the driving force behind the progression of business enterprises. Today, the data that is generated worldwide has grown ranging from terabytes to exabytes and petabytes, and the compounded rate of data further growing is much fast. The data generated widely has many forms and structures. The deluge of data generated, which is both valuable and challenging, along with emerging technologies and techniques that are used to handle it is referred to as the evolution and era of “Big Data”. As the big data is generated from multitudinous sources, majority of this data exists in unstructured form that demands specialized processing and storage capabilities, unlike the structured data that uses storage and processing of traditional relational structures. This results in high complexity and uncertainty in data. The usage of statistical analysis, computer-based models and quantitative methods that can help the business organizations to improve insights for better operations and decision-making is referred as business analytics. To work intelligently and focus on value generation, organizations need to focus on business analytics. The analytics are a critical component of big data computing. As defined in the literature, an intelligent enterprise has the characteristics similar to human nervous system and is responsive to external stimuli. To leverage the large volume of data for driving the business enterprises, timely and accurate insights derived out of the big data are a big challenge. The technologies like Hadoop and Apache Spark assist in handling big data on both fronts. However, handling and analysis of big data are a challenge for any organization with respect to its storage and technical expertise. Business analytics is used in business organizations for value generation by data manipulation along with business intelligence and report generation. Advanced analytics are also used by business enterprises that use techniques of data mining, data optimization and predictive forecasting.
KeywordsBig Data Data Analytics Hadoop V’s of Big Data Apache Spark
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