Integrating structured and unstructured data in a business-intelligence-system

The recent liberalization of the German energy market has forced the energy industry to develop and install new information systems to support agents on the energy trading floors in their analytical tasks. Besides classical approaches of building a data warehouse giving insight into the time series to understand market and pricing mechanisms, it is crucial to provide a variety of external data from the web. Weather information as well as political news or market rumors are relevant to give the appropriate interpretation to the variables of a volatile energy market. Starting from a multidimensional data model and a collection of buy and sell transactions a data warehouse is built that gives analytical support to the agents. Following the idea of web farming we harvest the web, match the external information sources after a filtering and evaluation process to the data warehouse objects, and present this qualified information on a user interface where market values are correlated with those external sources over the time axis.

Market, Management and Profession. Social Business in the Polder

In a recent policy document of the organized employers in the care and welfare sector in The Netherlands (the MO Group), directors and board members of care and welfare institutions present themselves as "social entrepreneurs", managing their institutions as look-a like commercial companies. They are hardly criticized and there is not any countervailing power of significance. The workers are focusing on their own specialized professional fields and divided as a whole. Many government officials are in favour or do not bother. The relatively small number of intellectual workers in Dutch care and welfare are fragmented and pragmatic. From a democratic point of view this is a worrying situation. From a professional point of view the purpose and functions of professional care and welfare work are at stake. The penetration of market mechanisms and the take-over by commercially orientated managers result from unquestioned adaptation of Anglo-Saxon policy in The Netherlands in the 1990's, following the crisis of the Welfare State in the late 1980's. The polder country is now confronted fully with the pressure and negative effects of unbalanced powers in the institutions, i.e. Managerialism. After years of silence, the two principal authentic critics of Dutch care and welfare, Harry Kunneman and Andries Baart, are no longer voices crying in the wilderness, but are getting a response from a growing number of worried workers and intellectuals. Kunneman and Baart warn against the restriction of professional space and the loss of normative values and standards in the profession. They are right. It is high time to make room for criticism and to start a debate about the future of the social professions in The Netherlands, better: in Europe. Research, discussion and action have to prove how worrying the everyday situation of professional workers is, what goals have to be set and what strategy to be chosen.

Open business intelligence: on the importance of data quality awareness in user-friendly data mining

Citizens demand more and more data for making decisions in their daily life. Therefore, mechanisms that allow citizens to understand and analyze linked open data (LOD) in a user-friendly manner are highly required. To this aim, the concept of Open Business Intelligence (OpenBI) is introduced in this position paper. OpenBI facilitates non-expert users to (i) analyze and visualize LOD, thus generating actionable information by means of reporting, OLAP analysis, dashboards or data mining; and to (ii) share the new acquired information as LOD to be reused by anyone. One of the most challenging issues of OpenBI is related to data mining, since non-experts (as citizens) need guidance during preprocessing and application of mining algorithms due to the complexity of the mining process and the low quality of the data sources. This is even worst when dealing with LOD, not only because of the different kind of links among data, but also because of its high dimensionality. As a consequence, in this position paper we advocate that data mining for OpenBI requires data quality-aware mechanisms for guiding non-expert users in obtaining and sharing the most reliable knowledge from the available LOD.

Empowering global software development with business intelligence

Context: Global Software Development (GSD) allows companies to take advantage of talent spread across the world. Most research has been focused on the development aspect. However, little if any attention has been paid to the management of GSD projects. Studies report a lack of adequate support for management’s decisions made during software development, further accentuated in GSD since information is scattered throughout multiple factories, stored in different formats and standards. Objective: This paper aims to improve GSD management by proposing a systematic method for adapting Business Intelligence techniques to software development environments. This would enhance the visibility of the development process and enable software managers to make informed decisions regarding how to proceed with GSD projects. Method: A combination of formal goal-modeling frameworks and data modeling techniques is used to elicitate the most relevant aspects to be measured by managers in GSD. The process is described in detail and applied to a real case study throughout the paper. A discussion regarding the generalisability of the method is presented afterwards. Results: The application of the approach generates an adapted BI framework tailored to software development according to the requirements posed by GSD managers. The resulting framework is capable of presenting previously inaccessible data through common and specific views and enabling data navigation according to the organization of software factories and projects in GSD. Conclusions: We can conclude that the proposed systematic approach allows us to successfully adapt Business Intelligence techniques to enhance GSD management beyond the information provided by traditional tools. The resulting framework is able to integrate and present the information in a single place, thereby enabling easy comparisons across multiple projects and factories and providing support for informed decisions in GSD management.

Design and development of agent-based procurement system to enhance business intelligence

The purpose of this research is to propose a procurement system across other disciplines and retrieved information with relevant parties so as to have a better co-ordination between supply and demand sides. This paper demonstrates how to analyze the data with an agent-based procurement system (APS) to re-engineer and improve the existing procurement process. The intelligence agents take the responsibility of searching the potential suppliers, negotiation with the short-listed suppliers and evaluating the performance of suppliers based on the selection criteria with mathematical model. Manufacturing firms and trading companies spend more than half of their sales dollar in the purchase of raw material and components. Efficient data collection with high accuracy is one of the key success factors to generate quality procurement which is to purchasing right material at right quality from right suppliers. In general, the enterprises spend a significant amount of resources on data collection and storage, but too little on facilitating data analysis and sharing. To validate the feasibility of the approach, a case study on a manufacturing small and medium-sized enterprise (SME) has been conducted. APS supports the data and information analyzing technique to facilitate the decision making such that the agent can enhance the negotiation and suppler evaluation efficiency by saving time and cost.

Systemological Bases of Business Intelligence

Sustainable development support, balanced scorecard development and business process modeling are viewed from the position of systemology. Extensional, intentional and potential properties of a system are considered as necessary to satisfy functional requirements of a meta-system. The correspondence between extensional, intentional and potential properties of a system and sustainable, unsustainable, crisis and catastrophic states of a system is determined. The inaccessibility cause of the system mission is uncovered. The correspondence between extensional, intentional and potential properties of a system and balanced scorecard perspectives is showed. The IDEF0 function modeling method is checked against balanced scorecard perspectives. The correspondence between balanced scorecard perspectives and IDEF0 notations is considered.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding

“La Business Intelligence per il monitoraggio delle vendite: il caso Ducati Motor Holding”. L’obiettivo di questa tesi è quello di illustrare cos’è la Business Intelligence e di mostrare i cambiamenti verificatisi in Ducati Motor Holding, in seguito alla sua adozione, in termini di realizzazione di report e dashboard per il monitoraggio delle vendite. L’elaborato inizia con una panoramica generale sulla storia e gli utilizzi della Business Intelligence nella quale vengono toccati i principali fondamenti teorici: Data Warehouse, data mining, analisi what-if, rappresentazione multidimensionale dei dati, costruzione del team di BI eccetera. Si proseguirà mediante un focus sui Big Data convogliando l’attenzione sul loro utilizzo e utilità nel settore dell’automotive (inteso nella sua accezione più generica e cioè non solo come mercato delle auto, ma anche delle moto), portando in questo modo ad un naturale collegamento con la realtà Ducati. Si apre così una breve overview sull’azienda descrivendone la storia, la struttura commerciale attraverso la quale vengono gestite le vendite e la gamma dei prodotti. Dal quarto capitolo si entra nel vivo dell’argomento: la Business Intelligence in Ducati. Si inizia descrivendo le fasi che hanno fino ad ora caratterizzato il progetto di Business Analytics (il cui obiettivo è per l'appunto introdurre la BI i azienda) per poi concentrarsi, a livello prima teorico e poi pratico, sul reporting sales e cioè sulla reportistica basata sul monitoraggio delle vendite.

Business Intelligence como soporte de las decisiones estratégicas, tácticas y operacionales de las organizaciones.

La importancia del proceso de toma de decisiones en la determinación del éxito de las compañías; genera la necesidad de contar con una fuente de información confiable que permita la generación de conocimiento oportuno y a disposición de quien lo necesita. El propósito de esta investigación es establecer un marco de referencia de la utilización de Business Intelligence como soporte de las decisiones tácticas, estratégicas y operacionales en las empresas. Iniciando con la descripción de la evolución de los sistemas de información utilizados en el proceso de toma de decisiones, impulsada por los diferentes cambios tecnológicos que han marcado el camino del establecimiento de Business Intelligence como una solución integral para los desafíos que se presentan a diario relacionados con la búsqueda de generación de valor mediante la implementación de decisiones óptimas. Luego se describe la arquitectura de un sistema de inteligencia de negocios en la cual se define elementos básicos para el correcto funcionamiento, como lo son: almacenamiento de datos, funciones empresariales, sistemas de gestión y las interfaces de usuario. Además de describir el proceso y alcance de su correcta implementación, y poder así obtener los beneficios que estos sistemas ofrecen. La metodología desarrollada en la investigación fue descriptiva, y se fundamentó en identificar el grado de utilización de Business Intelligence por los tomadores de decisiones, representados por egresados y graduados de la Maestría en Administración Financiera de la Universidad de El Salvador en el período 2006-2015.

Using business intelligence to support the process of organizational sensemaking

Making sense of an organization overwhelmed with data becomes a problem for decision makers at all levels of business planning and operation. Although scholars have suggested several technological solutions such as business intelligence as being useful in helping busy executives to make decisions, we still know little about assisting business stakeholders in the process of understanding their organizational complexity before such decisions could even be formulated. In this paper, we investigate the opportunities in using BI technologies to make sense of a business environment. We analyze the views and opinions of developers, analysts, consultants, and users of business intelligence, who are experienced in using the technology beyond decision making to support organizational sensemaking. Our results highlight the need for creating and maintaining individual; and organizational identity and enacting this identity on the business and its environment.

Supporting business intelligence usage: an integrated framework with automatic weighting

This paper presents an integrated framework that comprises an automatic weighting method for assessing data quality (DQ) of the framework so as to better support the business intelligence (BI) usage. Specifically, we utilize business process modeling (BPM) notation and information product map and frame them into a hierarchical mapping structure. Furthermore, we develop and demonstrate an automatic weight-assignment method for evaluating critical dimensions (i.e., completeness and accuracy) of DQ of the integrated framework. Through a design science paradigm, the effectiveness of the framework and the associated DQ weighting method has been rigorously validated by faculty management users of a university. The framework together with the DQ weighting method builds user confidence by enhancing the traceability of a BI product. The automatic DQ weight assignment also provides better time efficiency because the weight of each data attribute is determined automatically based on its usage on the BI dashboard.

Il passaggio dalla Business Intelligence all'Advanced Analytics: individuazione e analisi di un modello in merito all'influenza del lobbying nel sistema economico

I Big Data stanno guidando una rivoluzione globale. In tutti i settori, pubblici o privati, e le industrie quali Vendita al dettaglio, Sanità, Media e Trasporti, i Big Data stanno influenzando la vita di miliardi di persone. L’impatto dei Big Data è sostanziale, ma così discreto da passare inosservato alla maggior parte delle persone. Le applicazioni di Business Intelligence e Advanced Analytics vogliono studiare e trarre informazioni dai Big Data. Si studia il passaggio dalla prima alla seconda, mettendo in evidenza aspetti simili e differenze.

Using business intelligence to support the process of organizational sensemaking.

Morteza’s thesis investigated the opportunities in using BI technologies to make sense of a business environment. The results of his research highlighted the need for creating and maintaining an identity for Business Intelligence at both individual and organizational level and enacting this identity on the business and its environment.

Business intelligence em sistemas de apoio à gestão de frotas: Análise de Tecnologias e metodologias

O objecto de estudo desta tese de mestrado surgiu da necessidade de dar resposta a uma proposta para uma solução de business intelligence a pedido de um cliente da empresa onde até à data me encontro a desempenhar funções de analista programador júnior. O projecto consistiu na realização de um sistema de monitorização de eventos e análise de operações, portanto um sistema integrado de gestão de frotas com módulo de business intelligence. Durante o decurso deste projecto foi necessário analisar metodologias de desenvolvimento, aprender novas linguagens, ferramentas, como C#, JasperReport, visual studio, Microsoft SQL Server entre outros. ABSTRACT: Business Intelligence applied to fleet management systems - Technologies and Methodologies Analysis. The object of study of this master's thesis was the necessity of responding to a proposal for a business intelligence solution at the request of a client company where so far I find the duties of junior programmer. The project consisted of a system event monitoring and analysis of operations, so an integrated fleet management with integrated business intelligence. During the course of this project was necessary to analyze development methodologies, learn new languages, tools such as C #, JasperReports, visual studio, Microsoft Sql Server and others.