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Data engineering is the means for understanding a process. The data might be generated in many ways, or subset of the available data may use data analysis techniques from statistics, machine learning, pattern recognition or neural networks, together with other technologies such as visualization, optimization, database systems, prototyping tools and knowledge elicitation. The goal is to use the available data or generate more data and to thereby understand the process being investigated. The process of analysing the data, creating new analysis tools specifically for the task and working with the domain experts is a key aspect of this engineering task.