{'fraction_non_alphanumeric': 0.015549076773566569, 'fraction_numerical': 0.0, 'mean_word_length': 4.988372093023256, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Experimental Results on Change Data Capture Methods Implementation in Different Data Structures to Support Real Time Data Warehouse

The need for rapid decision making in the organisation, causing the importance of developing a real-time data warehouse system. In addition, what also needs to be considered is how to make the extract, transform, load (ETL) processes carried out, would not interfere the performance of the operational database being used. One of the methods that can be used is change data capture. Nowadays, the data sources that companies used for many operations are usually coming from different sources. The proposed research will identified which one is the best change data capture method from three types of methods in three database application for each type of data structure to be tested, that supports the RTDW system making process. From the results of research conducted it is proved that the best change data capture method is different for each type of data source tested in the same environment.