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Abstract
—In this project used to Actionable intelligence It means much more than simply finding or summarizing data; it stresses the discovery of hidden (unknown and hard to find)patterns that can be used to predict concepts, events, trends, opinions and so on to support decision makers.The expected use of actionable intelligence varies from system to system, with each variation increasing the complexity involved when engineering such systems. For this reason, it’s important to derive taxonomy for understanding actionable intelligence and for thinking about how it affects the complexity and development of big data software. The following three levels (L1, L2, L3) of actionable intelligence are proposed. (L1)Supervised actionable intelligence, (L2) Semi supervised actionable intelligence and (L3)Unsupervised actionable intelligence. The supervised system serves as decisionsupport for humans, so that humans supervise the intelligenceproduced by machines before takingaction. Semi supervised machines are relied upon to take actions based on self-produced intelligence; however, these actions can be reversed or corrected by humans. Unsupervised system machines are fully relied upon to take actions without requiring human intervention or correction.