Managing colossal extent of data can not only put a wrench on resources, but also prove to be an awfully pricey proposal. This framework brings all-encompassing, parallel computing jointly with commodity servers, enabling a considerable reduction in the expenses per terabyte of storage. It rules out trust on expensive, proprietary hardware and the need to uphold diverse systems to stock up on and process data. In addition, it is a fine alternative to the ‘Extract’, ‘Transform’ and ‘Load’ (ETL) process which heaves out data from different systems, changes it into a structure suitable for analysis and loads it onto a database.
As per our experts, fresh nodes can be added as per the user’s requirement. This adding up does not, nonetheless, alter the pre-existing data system, data modeling and accompanying functions.
Data Modeling – Working in a Framework
The framework is close to a complete modular, which means users can amend almost any of its mechanism for an unalike software tool. This makes the architecture flexible, brawny and well-organized. Its nimbleness also concerns the system it handles all sorts of statistics from incongruent systems. This data could be prearranged or nebulous, images, log files, audio files and email minutes, among other folder types. It also rules out any prerequisite for creating a schema to manage this data, which means users don’t have need of scrutinizing the data before storing it.
Call our data modeling experts to understand the entire process before implementing for your business!