Unstructured Data, NoSQL, and Terms Analytics

Lomotey, Richard K.; Deters, Ralph

doi:10.1007/978-3-319-30146-4_6

Cited by 2 publications

(1 citation statement)

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“…OLAP (online analytical processing) is a technique for processing and analyzing data. OLAP is a multidimensional structure that allows for quick access to data and advanced analysis [10,11]. Because traditional OLAPs are based on relational databases, Big Data analysis on NOSQL databases is difficult [12].…”

Section: Introductionmentioning

confidence: 99%

An Innovative Model for Extracting OLAP Cubes from NOSQL Database Based on Scalable Naïve Bayes Classifier

Davardoost

Sangar

Majidzadeh

2022

Mathematical Problems in Engineering

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Due to unstructured and large amounts of data, relational databases are no longer suitable for data management. As a result, new databases known as NOSQL have been introduced. The issue is that such a database is difficult to analyze. Online analytical processing (OLAP) is the foundational technology for data analysis in business intelligence. Because these technologies were designed primarily for relational database systems, performing OLAP in NOSQL is difficult. We present a model for extracting OLAP cubes from a document-oriented NOSQL database in this article. A scalable Naïve Bayes classifier method was used for this purpose. The proposed solution is divided into three stages of preparation, Naïve Bayes, and NBMR. Our proposed algorithm, NBMR, is based on the Naïve Bayes classifier (NBC) and the MapReduce (MR) programming model. Each NOSQL database document with nearly the same attribute will belong to the same class, and as a result, OLAP cubes can be used to perform data analysis. Because the proposed model allows for distributed and parallel Naïve Bayes Classifier computing, it is appropriate and suitable for large-scale data sets. Our proposed model is a proper and efficient approach when considering the speed and reduced the number of required comparisons.

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Section: Introductionmentioning

confidence: 99%