Review Paper on Platform for Big Data Analytics as a Service with Stock Market Prediction and Analysis

Shirish Mohan  Dubey; Bhavya  Natani; Charul  Tongaria; Aditya  Vijay; Ankit  Parakh

Abstract

Petabyte-scale data is referred to as big data. The sum of the data in this quantity, which includes audio files, image files, and many more. Due to the unstructured nature of the data, it is challenging to evaluate the information that is gathered from it. As a result of social networking and cloud computing, data has significantly increased. It is therefore difficult to assess, process, and store. Big data processing does not work well with conventional techniques. Utilising relational databases or conducting surveys are examples of traditional tactics. Big data platforms are crucial for improving the accuracy of the analysis phase. There are two main use cases of big data analytics. They are certainly the analysis of big volumes of data and including accurate prediction. The list of some of the most popular big data analytics tools is as follows: Data can be stored and analysed using Hadoop; MongoDB is used for datasets that change quickly; Talend is employed for data integration and management; The Cassandra is a distributed database, which controls data chunks; Spark is a technology for quickly processing and analysing enormous amounts of data; STORM is an open-source real-time computing platform; and Kafka, a system for fault-tolerant storage and distributed streaming.

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