Top Research Papers on Data Analytics

This research proposes a data analytics model for marketing decision making, which allows reducing the gap between competitors, regardless of their ownership structure.

The challenges associated with handling big data, including its volume, variety, and velocity, are discussed, and how data engineering and cleaning techniques are crucial for preparing data for analysis.

This research attempts to enable consultants to determine effective data analytics tasks for given business questions in order to answer those questions and be able to give companies advise.

How the WKU Initiative for Applied Data Analytics (ADA) can play a key role in helping YOU as a business organization or an environmental research entity make sense of YOUR data and how to best utilize it is described.

Data science and analytics have emerged as thriving fields as businesses and individuals produce massive volumes of data as a byproduct of online activity, and a growing need exists for professionals in these fields.

The use and its importance in the banking sector are explored, with special emphasis on fraud detection, and the usage and its fruitage is explained with the help of three case studies of this country.

Deep Brain Stimulation (DBS)—where electrodes placed in the brain give electric signals—initially seemed very beneficial to a patient combating the physical symptoms of Parkinson’s disease. However, his behavior changed significantly as well. The man started a relationship with a married woman and bought her a second home and a holiday home abroad.

Al giorno d’oggi l’analisi dei dati e una componente cruciale per comprendere patterns, predire comportamenti e scoprire errori in catene di montaggio complesse. Puo essere anche un tool di profiling. Nel caso di database grezzi con tante tabelle piene di dati, le informazioni sono difficili da estrarre e sembrano nascoste, ma in verita se i dati si possono organizzare in maniera leggibile a noi umani, e molto piu facile analizzare i pattern che sembrano nascosti. Lo scopo di questo progetto e quello di acquisire conoscenze in data analytics e poterle usare per riorganizzare i dati in diver...

This special theme issue of IEEE Potentials introduces the rapidly evolving area of data analytics, which encompasses data analysis, data fusion, data storage, data sources, infrastructure and technology, screening and filtering algorithms, machine learning, and complexity.

The primal focus of this thesis is predicting a particular disease using such enormous data, using the above mentioned data mining techniques, pre- processing (data cleaning, data reduction, etc.), classification, analysis, etc.

Analytics in a Big Data World reveals how to tap into the powerful tool of data analytics to create a strategic advantage and identify new business opportunities.

The awareness and readiness of business professionals regarding the importance of analytics in everyday business is examined to examine the awareness and readiness of business professionals regarding the importance of analytics.

This paper demonstrates the features and capabilities of IBM Watson Analytics and compares it with other tools in decision making in the field of business intelligence.

A review of literature both supportive and critical of human resource analytics is provided, the involvement of academia in implementing analytical practices is argued, and a case study is used to illustrate how quantitative tools may positively influence the management and development of human resources.

A brief guide to the analytics lifecycle, the expanding array of tools and technologies, and selecting the right data platform for your needs.

Data analytics projects can be like throwing darts in the dark. Problem‐centric thinking is vital, argue Vincent Charles, Ali Emrouznejad, Tatiana Gherman, and James Cochran

Mobile, ubiquitous, and immersive computing appear poised to transform visualization, data science, and data-driven decision making.

A General Introduction to Data Analytics is an essential guide to understand and use data analytics and contains an explanation of the intuition behind the basic data analytics techniques.

This chapter deals with various applications of data analytics which include applying an algorithmic or mechanical procedure to infer bits of knowledge, for instance, going through a few informational collections to search for significant connections between one another.

The main aim of this paper is to analyze the given soil and its corresponding properties which can be used to determine the soil fertility which is essential for agricultural purposes.