Big Data Optimization

Data optimization is the practice of changing an organization's data strategy to improve the speed and efficiency of data extraction, analysis, and use. The goal of optimization is to find the best acceptable answer given some conditions of the problem. For a problem, there may be different solutions, in order to compare them and choose the optimal solution; a function called the objective function is defined. The goal of optimization is to achieve the "best" design according to a set of priority criteria or constraints. These include factors such as maximizing productivity, strength, reliability, longevity, efficiency and utilization. Data optimization alleviates this problem by reorganizing datasets and filtering out inaccuracies and noise. The result is often a dramatic increase in the speed at which actionable information is extracted, analyzed, and delivered to decision makers.

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