Abstract
Corbion Group Netherlands B.V. is a company specialized in food ingredients such as lactic acid which involves fermentation process. Thus, a system was created to monitor on real-time fermentation process in order to gain insight and control of the process. This system is called Corbion Process Analysis System, or CorPAS. CorPAS covers many projects in Corbion, and in general, it extracts data from flat files, then transforms and loads the data into Power BI for data visualization. The data extraction still needs to be manually done by the users by opening the databases and copy all the data into flat files. CorPAS 2.0. was initiated to improve the previous system and add a new feature. Automated data extraction was successfully implemented with data transformation and visualization, alongside with implementation of a new feature, such as data science predictive modeling. The solution was built with R language and data visualization tool such as Power BI.
Highlights
In this digital era, everything is built upon data and has a large impact on everyday lives
In CorPAS 1.0., the data extraction was still not automated, where the users need to copy the data from database and paste it into an excel file
This paper describes the assigned tasks to develop CorPAS 2.0. such as implementation of new data flow, data science predictive modeling, and data visualization, alongside with newly added project for CorPAS called Waste Water Treatment System (WWTS)
Summary
In this digital era, everything is built upon data and has a large impact on everyday lives. Such as implementation of new data flow, data science predictive modeling, and data visualization, alongside with newly added project for CorPAS called Waste Water Treatment System (WWTS). The goals comprise creating data extraction, transformation, and loading; implementation of data science predictive model; and data visualization. R is used to make scripts to handle extract, transform, and load (ETL) process from raw data to data that is needed by the project or user. Some projects need to use CorPAS and apply a new feature like data science predictive modeling in the system. A predictive model needs to be created based on the related data by applying classification/machine learning algorithm. The WWTS project aims to apply predictive modeling in order to monitor the data trends and the relationships among parameters or data. Apriori is used within CorPAS system to get a better understanding of the data, in this case information about relations among parameters and to get which parameter on what range can result in good results of quality attribute parameters
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