Big Data Analytics: A Survey

Abstract

Internet-based programs and communication techniques have become widely used and respected in the IT industry recently. A persistent source of "big data," or data that is enormous in volume, diverse in type, and has a complicated multidimensional structure, is internet applications and communications. Today, several measures are routinely performed with no assurance that any of them will be helpful in understanding the phenomenon of interest in an era of automatic, large-scale data collection. Online transactions that involve buying, selling, or even investing are all examples of e-commerce. As a result, they generate data that has a complex structure and a high dimension. The usual data storage techniques cannot handle those enormous volumes of data. There is a lot of work being done to find ways to minimize the dimensionality of big data in order to provide analytics reports that are even more accurate and data visualizations that are more interesting. As a result, the purpose of this survey study is to give an overview of big data analytics along with related problems and issues that go beyond technology.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 8 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.