Big-Data-Based Techniques for Predictive Intelligence

Big-Data-Based Techniques for Predictive Intelligence

Dharmpal Singh (JIS College of Engineering, India), Madhusmita Mishra (JIS College of Engineering, India) and Sudipta Sahana (JIS College of Engineering, India)
Copyright: © 2019 |Pages: 18
DOI: 10.4018/978-1-5225-6210-8.ch001


Big-data-analyzed finding patterns derive meaning and make decisions on data to produce responses to the world with intelligence. It is an emerging area used in business intelligence (BI) for competitive advantage to analyze the structured, semi-structured, and unstructured data stored in different formats. As the big data technology continues to evolve, businesses are turning to predictive intelligence to deepen the engagement to customers with optimization in processes to reduce the operational costs. Predictive intelligence uses sets of advanced technologies that enable organizations to use data stored in real time that move from a historical and descriptive view to a forward-looking perspective of data. The comparison and other security issue of this technology is covered in this book chapter. The combination of big data technology and predictive analytics is sometimes referred to as a never-ending process and has the possibility to deliver significant competitive advantage. This chapter provides an extensive review of literature on big data technologies and its usage in the predictive intelligence.
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The authors (Agarwal & Dhar, 2014) opined that magnitude of data generated and shared by businesses, public administrations numerous industrial and not-to-profit sectors, and scientific research, has increased immeasurably in form of textual content (i.e. structured, semistructured as well as unstructured) and multimedia content (e.g. videos, images, audio) on a multiplicity of platforms (e.g. machine-to-machine communications, social media sites, sensors networks, cyber-physical systems, and Internet of Things [IoT]). According the report of Dobre and Xhafa (2014), every day the world produces around 2.5 quintillion bytes of data (i.e. 1 exabyte equals 1 quintillion bytes or 1 exabyte equals 1 billion igabytes), with 90% of these data generated in the world being unstructured.

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