Big Data Analytic Framework for Organizational Leverage

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Towards the optimization of a parallel streaming engine for telco applications

Parallel and distributed computing is becoming essential to process in real time the increasingly massive volume of data collected by telecommunications companies. Existing computational paradigms such as MapReduce (and its popular open-source implementation Hadoop) provide a scalable, fault tolerant mechanism for large scale batch computations. However, many applications in the telco ecosystem require a real time, incremental streaming approach to process data in real time and enable proactive care. Storm is a scalable, fault tolerant framework for the analysis of real time streaming data. In this paper we provide a motivation for the use of real time streaming analytics in the telco ecosystem. We perform an experimental investigation into the performance of Storm, focusing in particular on the impact of parameter configuration. This investigation reveals that optimal parameter choice is highly non-trivial and we use this as motivation to create a parameter configuration engine. As first steps towards the creation of this engine we provide a deep analysis of the inner workings of Storm and provide a set of models describing data flow cost, central processing unit (CPU) cost, and system management cost. ©2014 Alcatel-Lucent

A review of natural language processing in contact centre automation

Contact centres have been highly valued by organizations for a long time. However, the COVID-19 pandemic has highlighted their critical importance in ensuring business continuity, economic activity, and quality customer support. The pandemic has led to an increase in customer inquiries related to payment extensions, cancellations, and stock inquiries, each with varying degrees of urgency. To address this challenge, organizations have taken the opportunity to re-evaluate the function of contact centres and explore innovative solutions. Next-generation platforms that incorporate machine learning techniques and natural language processing, such as self-service voice portals and chatbots, are being implemented to enhance customer service. These platforms offer robust features that equip customer agents with the necessary tools to provide exceptional customer support. Through an extensive review of existing literature, this paper aims to uncover research gaps and explore the advantages of transitioning to a contact centre that utilizes natural language solutions as the norm. Additionally, we will examine the major challenges faced by contact centre organizations and offer reco

Data Analytics in advancing Accounting Profession and Business Information for Decision Making

The nature of the risks and opportunities facing business has changed over time. Much of the global value today is more of technology service and knowledge based than it was 40 years ago. The study examines data analytics in advancing accounting profession and business information for decision making. Two specific objectives guided the study, the study used a survey research design approach, and the population consists of 300 respondents made up of 50 each from academics, financial analysts, accountants, business owners, investors and big data analysts. Descriptive statistics was used to analyses the data while Z test was used to test the hypotheses. The findings from the study shows that the two hypotheses tested has a high acceptance degrees level of an average percentage of (92.4%) and (86.98%) respectively, this goes to shows that the issue of big data analytics in advancing accounting profession and business information for decision making is very much germen. This also was observed in the results of Z-Test of the Standard Deviation of (0.412) and (0.303) respectively, which leads to the acceptance of the two alternatives hypotheses and rejecting of the null hypotheses. The study concluded that big data analytics improves and help business organizations take informed decisions to enhance their operational efficiency, also, that the world accepted the slogan that data is the new oil. Those who are able to gain out of that will remain in the business ie, survival of the fittest. This is the implication to the new millennium environment where the professional accountant finds itself. Therefore, should be able to deal with the complex procedures, so that the accountant will be a big data analytics professional too. The study recommended among others that all the stakeholders (academics, financial analysts, professional association bodies, accountants, business owners, investors and government) should be involves in the necessity of teaching big data and business analyses in management sciences in our higher institutions to promote students' knowledge, the continues enlightenment, holding workshops, training and retraining  courses for researchers and academics of the importance of analyzing big data and how to process, store, manage and use the analyzed data in the financial and accounting field, since using big data can lead to better disclosure which in turn  enhance investor trust