Aggregation Method To Handle Big Data For Gas Compressor

Time-based aggregation is important when dealing with massive data. Missing values in
the dataset also are one of the main problems that face operational data. There are a lot
of ways and methods to deal with time-series data with missing values. Thus, this
research is made to deepen the understanding of the current optimization workflow for
data aggregation focusing on the operation dataset. The preliminary study has been
conducted by a run through all the software integration between the project workflow.
This project will develop a dashboard with some features of toggling the time frame
functionality against the predictive model result which will evaluate the optimization
performance of the proposed data preprocessing workflow through measuring the
prediction accuracy vs aggregated and non-aggregate value.