Big data metadata classification
Abstract
Now there are a lot of data of different structure (or not structured at all) and origin, their volumes are growing exponentially. The problem is the existing software and hardware are not able to cope with so many different types of data appearing with great speed. Big Data has become too complex and dynamic to process, store, analyze and manage with traditional tools. It caused the appearance of new platforms and approaches for working with data, and at the same time, an understanding of the fact that to solve big data problems, these raw data must be supplemented with metadata. Metadata in this case is a means of classifying, organizing, and characterizing data and its content. Their main advantage is an ordered structure. Due to it, metadata is readable not only by a person, but also by a computer. Thus, they can be processed automatically and used for indexing, searching, combining, automated processing, classification of big data, etc. The creation of effective metadata management systems, first of all, requires their coordinated general classification that take into account the types of data sources (methods of their obtaining) that form the content, tasks solved at different stages of the life cycle, existing formats of data presentation, principles of reasonable efficiency, since often metadata size significantly exceeds the amount of described data (even big). Therefore, the aim of this work is to analyze existing sources of big data, methods for creating and processing the corresponding metadata, as well as software products that allow them to be processed in a certain way, and building the classification of metadata on the basis of the analysis.
Problems in programming 2019; 4: 53-74
Keywords
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PDF (Українська)References
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DOI: https://doi.org/10.15407/pp2019.04.053
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