A Review of analytics platform architecture in a Diversified Approach for Big Data Techniques | Original Article
The rapid climb of the latest technologies, modernization of application, and therefore the dimensionless growth of communication industries produces a multivolume of data every year. Data comes from various sources at different rates. It's impossible to use traditional data management strategies because of the complexity of big data. The new age of big data is a result of this. Big data is here to stay. On the other hand, Traditional data Analytics, are incapable of dealing with such enormous data volumes. The challenges that arise right now are how to establish a high-efficiency system for big data analysis how to design an appropriate mining algorithm to discover important objects in vast data. The development of big data applications has risen in importance over the last several years. Data mining is being used by an increasing number of firms across a broad variety of sectors to obtain meaningful insights. This study focuses on the analytical perspectives expressed by several academics in the field of huge data. This article begins with a basic overview of data analytics and then moves on to a discussion of big data analytics. The majority of its focus is on the platform's key elements and applications, as well as a few huge data concerns. Several crucial unsolved challenges and research objectives will also be presented for the next step in big data analytics.