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Название: Data Fabric Architectures: Web-Driven Applications
Автор: Vandana Sharma, Balamurugan Balusamy, J. Joshua Thomas
Издательство: De Gruyter
Год: 2023
Страниц: 228
Язык: английский
Формат: pdf (true), epub
Размер: 58.2 MB

The immense increase on the size and type of real time data generated across various edge computing platform results in unstructured databases and data silos. This edited book gathers together an international set of researchers to investigate the possibilities offered by data-fabric solutions; the volume focuses in particular on data architectures and on semantic changes in future data landscapes.

There is a huge research gape between the traditional data fabrics, its Virtualization tools and the advanced and best tools in today’s date. Getting aroused with this fact this research is written to through light on the data fabrics and there are many data Virtualization tools available, and we’ve done the research to determine the best for small businesses. These tools should be versatile, easy to use and allow you to visualize data in a variety of ways to suit your business needs. The research clearly distinguishes the pros and cons of particular tool used in the research.

Big Data platform components like Hadoop, data lakes, and NoSQL have made Big Data architectures more logical, enabling businesses to pursue insight-driven competitive advantage. Moving corporate data to these platforms, especially when dealing with distributed data across data centers, is hampered by security issues, complicated data structures, issues with moving historical data, big volumes, latency issues, and variable speed of ingestion. In contrast to a unified platform for insights, we discovered that the majority of enterprises are developing various repositories and platforms. One of the techniques that can assist in identifying probable in the social and medical sciences is a statistical tool. Using statistical techniques, it is possible to identify data creation a mixture of data sets from legitimate and false.

Contributors include an international panel of leading researchers.
Describes Web-driven Data Fabric operations and solutions for Industry 4.0.
Includes data harvesting and visualization tools for Scalable Data Fabric in current market trends.





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