Data Standardization and Analysis Model for Enhanced Global Productivity

摘要

Every organization needs to effectively manage its data collection and analysis process in order to efficiently collaborate on a global scale. This paper describes a model for standardizing the data collection and analysis process and specifically deals with two challenges in this regard: 1) A method for standardization of the nomenclature of different physical parameters measured during a typical engine test. This is essential for processing data from facilities spread across the globe to run them through a standard set of calculations. The process of storing and performing a given set of complex processes on the data while allowing analysts to view the steps of the processing in a transparent intuitive manner is also described in the paper. 2) Building on the first point, the paper also describes a process for performing a standard set of data quality checks on data as it is being collected. This allows for detection of issues in the data on a real-time basis. The paper further describes how this process can be applied to analyzing data and reporting issues while running a transient test in which the engine is rapidly changing its state every second.