Examining Heterogeneity Structured on a Large Data Volume with Minimal Incompleteness.

Whereas Big Data analytics can provide a variety of benefits, processing heterogeneous data comes with its own set of limitations. A transaction pattern must be studied independently while working with Bitcoin (BTC) data. Hence, this study examines twitter data related to BTC and investigate communications pattern on BTC transactional tweet. Using the hashtags #BTC or #BTC on Twitter, a vast amount of data was gathered, which was mined to uncover a pattern that everyone either (speculators, teaches, or the stakeholders) uses on Twitter to discuss BTC transactions. This aim is to determine the direction of BTC transaction tweets based on historical data. As a result, this research proposes using Big Data analytics to track BTC transaction communications in tweets in order to discover a pattern. Hadoop platform MapReduce was used. The finding indicate that in the map step of the procedure, Hadoop's tokenize the dataset and parse them to the mapper where thirteen patterns were established and reduced to three patterns using the attributes previously stored data in the Hadoop context, one of which is the Emoji data that was left out in previous research discussions, but the text is only one piece of the puzzle on BTC transaction interaction, and the key part of it is "No certainty, only possibilities" in BTC transactions. [ABSTRACT FROM AUTHOR]