Data Warehouse Design and Management: Theory and Practice

The need to store data and information permanently, for their reuse in later stages, is a very relevant problem in the modern world and now affects a large number of people and economic agents. The storage and subsequent use of data can indeed be a valuable source for decision making or to increase commercial activity. The next step to data storage is the efficient and effective use of information, particularly through the Business Intelligence, at whose base is just the implementation of a Data Warehouse. In the present paper we will analyze Data Warehouses with their theoretical models, and illustrate a practical implementation in a specific case study on a pharmaceutical distribution companyData warehouse, database, data model.

Relatório de Estágio - Solução de BI Roaming Data Science (RoaDS) em ambiente Vodafone

A telecom company (Vodafone), had the need to implement a Business Intelligence solution for Roaming data across a wide set of different data sources. Based on the data visualization of this solution, its key users with decision power, can make a business analysis and needs of infrastructure and software expansion. This document aims to expose the scientific papers produced with the various stages of production of the solution (state of the art, architecture design and implementation results), this Business Intelligence solution was designed and implemented with OLAP methodologies and technologies in a Data Warehouse composed of Data Marts arranged in constellation, the visualization layer was custom made in JavaScript (VueJS). As a base for the results a questionnaire was created to be filled in by the key users of the solution. Based on this questionnaire it was possible to ascertain that user acceptance was satisfactory. The proposed objectives for the implementation of the BI solution with all the requirements was achieved with the infrastructure itself created from scratch in Kubernetes. This BI platform can be expanded using column storage databases created specifically with OLAP workloads in mind, removing the need for an OLAP cube layer. Based on Machine Learning algorithms, the platform will be able to perform the predictions needed to make decisions about Vodafone's Roaming infrastructure

Method Support of Information Requirements Analysis for Analytical Information Systems: State of the Art, Practice Requirements, and Research Agenda

Due to specific characteristics of analytical information systems, their development varies significantly from transaction-oriented systems. Specific method support is particularly needed for requirements engineering and its information-related component, information requirements analysis. The paper at hand first evaluates the state of the art and identifies necessary method support extensions. On this basis, method support requirements for information requirements engineering are identified. The survey is structured along the five core activities of traditional requirements engineering. It reveals a need for further research especially on information requirements elicitation, validation, and management. It further contributes to a discussion of aspects that should be considered by any method support. Due to comparatively long life cycles of analytical information systems, the introduction of a process perspective is discussed in order to ensure the continuous elicitation, documentation, and management of information requirement

Method Support of Information Requirements Analysis for Analytical Information Systems State of the Art, Practice Requirements, and Research Agenda

Due to specific characteristics of analyticalinformation systems, their developmentvaries significantly from transaction-oriented systems. Specific methodsupport is particularly needed forrequirements engineering and itsinformation-related component, informationrequirements analysis. The paperat hand first evaluates the state ofthe art and identifies necessary methodsupport extensions.On this basis,methodsupport requirements for informationrequirements engineering are identified.The survey is structured alongthe five core activities of traditional requirementsengineering. It reveals aneed for further research especially oninformation requirements elicitation,validation, and management. It furthercontributes to a discussion of aspectsthat should be considered by anymethod support. Due to comparativelylong life cycles of analytical informationsystems, the introduction of a processperspective is discussed in order to ensurethe continuous elicitation, documentation,and management of informationrequirements

Organizing Data Governance: Findings from the Telecommunications Industry and Consequences for Large Service Providers

Many companies see Data Governance as a promising approach to ensuring data quality and maintaining its value as a company asset. While the practitioners’ community has been vigorously discussing the topic for quite some time, Data Governance as a field of scientific study is still in its infancy. This article reports on the findings of a case study on the organization of Data Governance in two large telecommunications companies, namely BT and Deutsche Telekom. The article proposes that large, service-providing companies in general have a number of options when designing Data Governance and that the individual organizational design is context-contingent. Despite their many similarities, BT and Deutsche Telekom differ with regard to their Data Governance organization. BT has followed a more project-driven, bottom-up philosophy; Deutsche Telekom, on the other hand, favors a rather constitutive, top-down approach. The article also proposes a research agenda for further studies in the field of Data Governance organization

Churn Modeling In Telecommunications Sector

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2006Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2006Bu tezde yapılan çalışma Türk iletişim sektörüne yöneliktir. Bu teze konu olan mobil iletişim şirketi, eğer kontörlü bir hat son kontör yüklemesinden sonra 6 ay içinde tekrar kontör yüklemezse, bu müşterinin kontratını iptal eder. Bu çalışma, söz konusu mobil iletişim şirketinden ayrılacak müşterilerin tahmininin veri madenciliği teknikleri ile modellenmesi ve bu sayede her müşteriye bir puan atanmasını kapsar. Bu puan, müşterinin 6 ay sonra şirketi terk etme olasılığını gösterir. Her veri madenciliği uygulaması arkasında çalışan algoritmalar vardır. Karar ağaçları ve regresyon modellemesi ayrılacak müşterilerin tahmini sırasında kullanılmış ve bu algoritmalar tez içinde ayrıntılı olarak sunulmuştur. Kontörlü hatta sahip müşterilerin geçen ay çağrı merkezine yaptıkları şikayet sayısı, bir bağlılık programına üye olmaları, son 6 aydaki kontör yükleme sayıları ve geçen ay bu mobil şirketin şebekesinde aradıkları farklı kişi sayısı müşterilerin şirketten ayrılma tahmininde önemli birer gösterge olarak ortaya çıkmıştır. Bu çalışmada hangi müşterilerin gideceği bulunduktan sonra, gitme ihtimali yüksek kontörlü müşterilerin elde tutulması ile şirkete sağladıkları katkı değerlendirilmiştir. Müşteri ilişkileri yönetiminde erken önlem alınabilmesi için, gitme ihtimalini gösteren olasılık değerlerinin nasıl kullanılabileceği konusunda önerilerde bulunulmuştur.This thesis focuses on the wireless telecommunications sector in Turkey. If a prepaid customer does not refill his/her card within 6 months after his/her last refill, the wireless company subject to this study cancels the contract of the prepaid customer. A churn prediction model is developed to produce a score for each prepaid individual customer who is likely leave the company in 6 months due to this involuntary reason. Logistic regression and decision trees are used to predict the churners. All the algorithms that are employed in this study are illustrated in detail. Number of complaint calls done by the customer to Call Center for last month, being a member of loyalty program, total number of refills of the customer for last 6 months and number of different phone numbers that customer dialed last month in the network of this wireless company have been found as most significant indicators of prepaid churn. After determining which customers are likely to churn, this study ends with assessing churners value to the organization and provides recommendations on how to use churn scores in order to show the importance of proactive customer relationship management.Yüksek LisansM.Sc

ENHANCEMENT OF CHURN PREDICTION ALGORITHMS

Customer churn can be described as the process by which consumers of goods and services discontinue the consumption of a product or service and switch over to a competitor.It is of great concern to many companies. Thus, decision support systems are needed to overcome this pressing issue and ensure good return on investments for organizations. Decision support systems use analytical models to provide the needed intelligence to analyze an integrated customer record database to predict customers that will churn and offer recommendations that will prevent them from churning. Customers churn prediction, unlike most conventional business intelligence techniques, deals with customer demographics, net worth-value, and market opportunities. It is used in determining customers who are likely to churn, those likely to remain loyal to the organization, and for prediction of future churn rates. Customer defection is naturally a slow rate event, and it is not easily detected by most business intelligent solutions available in the market; especially when data is skewed, large, and distinct. Thus, accurate and precise prediction methods are needed to detect the churning trend. In this study, a churn model that applies business intelligence techniques to detect the possibility that a customer will churn using churn trend analysis of customer records is proposed. The model applies clustering algorithms and enhanced SPRINT decision tree algorithms to explore customer record database, and identify the customer profile and behavior patterns. The Model then predicts the possibility that a customer will churn. Additionally, it offers solutions for retaining customers and making them loyal to a business entity by recommending customer-relationship management measures