On advancing business intelligence in the electricity retail market

In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

Business Intelligence Competency Centerin perustaminen: Case LähiTapiola

Tässä diplomityössä selvitetään case-tutkimuksena parhaita käytäntöjä Business Intelligence Competency Centerin (BICC) eli liiketoimintatiedonhallinnan osaamiskeskuksen perustamiseen. Työ tehdään LähiTapiolalle, jossa on haasteita BI-alueen hallinnoinnissa kehittämisen hajaantuessa eri yksiköihin ja yhtiöihin. Myös järjestelmäympäristö on moninainen. BICC:llä tavoitellaan parempaa näkyvyyttä liiketoiminnan tarpeisiin ja toisaalta halutaan tehostaa tiedon hyödyntämistä johtamisessa sekä operatiivisen tason työskentelyssä. Tavoitteena on lisäksi saada kustannuksia pienemmäksi yhtenäistämällä järjestelmäympäristöjä ja BI-työkaluja kuten myös toimintamalleja. Työssä tehdään kirjallisuuskatsaus ja haastatellaan asiantuntijoita kolmessa yrityksessä. Tutkimuksen perusteella voidaan todeta, että liiketoiminnan BI-tarpeita kannattaa mahdollistaa eri tasoilla perusraportoinnista Ad-hoc –raportointiin ja edistyneeseen analytiikkaan huomioimalla nämä toimintamalleissa ja järjestelmäarkkitehtuurissa. BICC:n perustamisessa liiketoimintatarpeisiin vastaaminen on etusijalla.

Business Intelligence: Microsoft Power BI

Työn tavoitteena on tutkia Business Intelligencen ja BI-työkalujen vaatimusten kehittymistä viime vuosien aikana ja tutkia miten Microsoft Power BI -ohjelmisto vastaa modernin päätöksenteon tarpeisiin. Työ on toteutettu suurimmalta osin kirjallisuuskatsauksena, minkä lisäksi Microsoft Power BI:n toiminnallisuutta on tutkittu käytännössä käyttäen ohjelmiston ilmaisversiota. Tutkimuksessa on havaittu, että tiedon lähteiden määrän ja datan monimuotoisuuden kasvaessa on syntynyt tarve uusille, tehokkaille BI-järjestelmäratkaisuille, jotka hyödyntävät uudenlaisia menetelmiä. Modernissa BI 2.0 -mallissa korostuvat kehittyneemmän verkkoinfrastruktuurin ja ohjelmistotekniikan täysi hyödyntäminen, käytön helppous, tiedon tuottaminen ja jakaminen massoille, tiedon rikastamisen mahdollistaminen ja visualisoinnin ja interaktiivisuuden keskeinen asema tiedon tulkinnassa. Tutkimuksen perusteella Microsoft Power BI vaikuttaisi täyttävän keskeneräisyydestään ja muutamista tiedonhallinnallisista puutteistaan huolimatta lähes kaikki toimivan BI 2.0 -järjestelmän määritelmistä. Ohjelmisto tarjoaa riittävät analyyttiset ja esitystekniset työkalut useimpien tyypillisten käyttäjien tarpeisiin, minkä lisäksi paranneltu Location Intelligence -ratkaisu sekä uudet Q&A ja nopea oivallus -toiminnot luovat mielenkiintoisen tavan selata dataa. Jää nähtäväksi, miten ratkaisu kehittyy vielä tulevaisuudessa.

Design of a unified data with business rules storage model for OLTP and OLAP systems

This paper reviews the literature concerning the practice of using Online Analytical Processing (OLAP) systems to recall information stored by Online Transactional Processing (OLTP) systems. Such a review provides a basis for discussion on the need for the information that are recalled through OLAP systems to maintain the contexts of transactions with the data captured by the respective OLTP system. The paper observes an industry trend involving the use of OLTP systems to process information into data, which are then stored in databases without the business rules that were used to process information and data stored in OLTP databases without associated business rules. This includes the necessitation of a practice, whereby, sets of business rules are used to extract, cleanse, transform and load data from disparate OLTP systems into OLAP databases to support the requirements for complex reporting and analytics. These sets of business rules are usually not the same as business rules used to capture data in particular OLTP systems. The paper argues that, differences between the business rules used to interpret these same data sets, risk gaps in semantics between information captured by OLTP systems and information recalled through OLAP systems. Literature concerning the modeling of business transaction information as facts with context as part of the modelling of information systems were reviewed to identify design trends that are contributing to the design quality of OLTP and OLAP systems. The paper then argues that; the quality of OLTP and OLAP systems design has a critical dependency on the capture of facts with associated context, encoding facts with contexts into data with business rules, storage and sourcing of data with business rules, decoding data with business rules into the facts with the context and recall of facts with associated contexts. The paper proposes UBIRQ, a design model to aid the co-design of data with business rules storage for OLTP and OLAP purposes. The proposed design model provides the opportunity for the implementation and use of multi-purpose databases, and business rules stores for OLTP and OLAP systems. Such implementations would enable the use of OLTP systems to record and store data with executions of business rules, which will allow for the use of OLTP and OLAP systems to query data with business rules used to capture the data. Thereby ensuring information recalled via OLAP systems preserves the contexts of transactions as per the data captured by the respective OLTP system.

Optimized Water Demand Management Through Intelligent Sensing And Analytics: The WISDOM Approach

New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.

Tecniche, metodologie e strumenti per la Web Analytics, con particolare attenzione sulla Video Analytics

In questa tesi viene affrontato il tema del tracciamento video, analizzando le principali tecniche, metodologie e strumenti per la video analytics. L'intero lavoro, è stato svolto interamente presso l'azienda BitBang, dal reperimento di informazioni e materiale utile, fino alla stesura dell'elaborato. Nella stessa azienda ho avuto modo di svolgere il tirocinio, durante il quale ho approfondito gli aspetti pratici della web e video analytics, osservando il lavoro sul campo degli specialisti del settore e acquisendo familiarità con gli strumenti di analisi dati tramite l'utilizzo delle principali piattaforme di web analytics. Per comprendere a pieno questo argomento, è stato necessario innanzitutto conoscere la web analytics di base. Saranno illustrate quindi, le metodologie classiche della web analytics, ovvero come analizzare il comportamento dei visitatori nelle pagine web con le metriche più adatte in base alle diverse tipologie di business, fino ad arrivare alla nuova tecnica di tracciamento eventi. Questa nasce subito dopo la diffusione nelle pagine dei contenuti multimediali, i quali hanno portato a un cambiamento nelle modalità di navigazione degli utenti e, di conseguenza, all'esigenza di tracciare le nuove azioni generate su essi, per avere un quadro completo dell'esperienza dei visitatori sul sito. Non sono più sufficienti i dati ottenuti con i tradizionali metodi della web analytics, ma è necessario integrarla con tecniche nuove, indispensabili se si vuole ottenere una panoramica a 360 gradi di tutto ciò che succede sul sito. Da qui viene introdotto il tracciamento video, chiamato video analytics. Verranno illustrate le principali metriche per l'analisi, e come sfruttarle al meglio in base alla tipologia di sito web e allo scopo di business per cui il video viene utilizzato. Per capire in quali modi sfruttare il video come strumento di marketing e analizzare il comportamento dei visitatori su di esso, è necessario fare prima un passo indietro, facendo una panoramica sui principali aspetti legati ad esso: dalla sua produzione, all'inserimento sulle pagine web, i player per farlo, e la diffusione attraverso i siti di social netwok e su tutti i nuovi dispositivi e le piattaforme connessi nella rete. A questo proposito viene affrontata la panoramica generale di approfondimento sugli aspetti più tecnici, dove vengono mostrate le differenze tra i formati di file e i formati video, le tecniche di trasmissione sul web, come ottimizzare l'inserimento dei contenuti sulle pagine, la descrizione dei più famosi player per l'upload, infine un breve sguardo sulla situazione attuale riguardo alla guerra tra formati video open source e proprietari sul web. La sezione finale è relativa alla parte più pratica e sperimentale del lavoro. Nel capitolo 7 verranno descritte le principali funzionalità di due piattaforme di web analytics tra le più utilizzate, una gratuita, Google Analytics e una a pagamento, Omniture SyteCatalyst, con particolare attenzione alle metriche per il tracciamento video, e le differenze tra i due prodotti. Inoltre, mi è sembrato interessante illustrare le caratteristiche di alcune piattaforme specifiche per la video analytics, analizzando le più interessanti funzionalità offerte, anche se non ho avuto modo di testare il loro funzionamento nella pratica. Nell'ultimo capitolo vengono illustrate alcune applicazioni pratiche della video analytics, che ho avuto modo di osservare durante il periodo di tirocinio e tesi in azienda. Vengono descritte in particolare le problematiche riscontrate con i prodotti utilizzati per il tracciamento, le soluzioni proposte e le questioni che ancora restano irrisolte in questo campo.

Progettazione e sviluppo di una soluzione Hadoop per il calcolo di Big Data Analytics

Il presente elaborato ha come oggetto la progettazione e lo sviluppo di una soluzione Hadoop per il Calcolo di Big Data Analytics. Nell'ambito del progetto di monitoraggio dei bottle cooler, le necessità emerse dall'elaborazione di dati in continua crescita, ha richiesto lo sviluppo di una soluzione in grado di sostituire le tradizionali tecniche di ETL, non pi�ù su�fficienti per l'elaborazione di Big Data. L'obiettivo del presente elaborato consiste nel valutare e confrontare le perfomance di elaborazione ottenute, da un lato, dal flusso di ETL tradizionale, e dall'altro dalla soluzione Hadoop implementata sulla base del framework MapReduce.

E-CRM e a influência da digital analytics.

O mercado consumidor passou por diversas transformações ao longo do tempo devido principalmente à evolução tecnológica. A evolução tecnológica proporcionou ao consumidor a possibilidade de escolher por produtos e marcas, e permite a oportunidade de colaborar e influenciar a opinião de outros consumidores através do compartilhamento de experiências, principalmente através da utilização de plataformas digitais. O CRM (gerenciamento do relacionamento com o consumidor) é a forma utilizada pelas empresas para conhecerem o consumidor e criar um relacionamento satisfatório entre empresa e consumidor. Esse relacionamento tem o intuito de satisfazer e fidelizar o consumidor, evitando que ele deixe de consumir a marca e evitando que ele influencie negativamente outros consumidores. O e-CRM é o gerenciamento eletrônico do relacionamento com o consumidor, que possui todas as tradicionais características do CRM, porém com o incremento do ambiente digital. O ambiente digital diminuiu a distância entre pessoas e empresas e se tornou um meio colaborativo de baixo custo de interação com o consumidor. Por outro lado, este é um meio onde o consumidor deixa de ser passivo e se torna ativo, o que o torna capaz de influenciar não só um pequeno grupo de amigos, mas toda uma rede de consumidores. A digital analytics é a medição, coleta, análise e elaboração de relatórios de dados digitais para os propósitos de entendimento e otimização da performance em negócios. A utilização de dados digitais auxilia no desenvolvimento do e-CRM através da compreensão do comportamento do consumidor em um ambiente onde o consumidor é ativo. O ambiente digital permite um conhecimento mais detalhado dos consumidores, baseado não somente nos hábitos de compra, mas também nos interesses e interações. Este estudo tem como objetivo principal compreender como as empresas aplicam os conceitos do e-CRM em suas estratégias de negócios, compreendendo de que forma a digital analytics contribui para o desenvolvimento do e-CRM, e compreendendo como os fatores críticos de sucesso (humano, tecnológico e estratégico) impactam na implantação e desenvolvimento do e-CRM. Quatro empresas de diferentes segmentos foram estudadas através da aplicação de estudo de caso. As empresas buscam cada vez mais explorar as estratégias de e-CRM no ambiente digital, porém existem limitações identificadas devido à captação, armazenamento e análise de informações multicanais, principalmente considerando os canais digitais. Outros fatores como o apoio da alta direção e a compreensão de funcionários para lidar com estratégias focadas no consumidor único também foram identificados neste estudo. O estudo foi capaz de identificar as informações mais relevantes para a geração de estratégias de gerenciamento eletrônico do relacionamento com o consumidor e identificou os aspectos mais relevantes dos fatores críticos de sucesso.

Progettazione e Sviluppo di un Sistema di Proactive Alerting all'interno di una piattaforma di Big Data Analytics

Il lavoro presentato in questo elaborato tratterà lo sviluppo di un sistema di alerting che consenta di monitorare proattivamente una o più sorgenti dati aziendali, segnalando le eventuali condizioni di irregolarità rilevate; questo verrà incluso all'interno di sistemi già esistenti dedicati all'analisi dei dati e alla pianificazione, ovvero i cosiddetti Decision Support Systems. Un sistema di supporto alle decisioni è in grado di fornire chiare informazioni per tutta la gestione dell'impresa, misurandone le performance e fornendo proiezioni sugli andamenti futuri. Questi sistemi vengono catalogati all'interno del più ampio ambito della Business Intelligence, che sottintende l'insieme di metodologie in grado di trasformare i dati di business in informazioni utili al processo decisionale. L'intero lavoro di tesi è stato svolto durante un periodo di tirocinio svolto presso Iconsulting S.p.A., IT System Integrator bolognese specializzato principalmente nello sviluppo di progetti di Business Intelligence, Enterprise Data Warehouse e Corporate Performance Management. Il software che verrà illustrato in questo elaborato è stato realizzato per essere collocato all'interno di un contesto più ampio, per rispondere ai requisiti di un cliente multinazionale leader nel settore della telefonia mobile e fissa.

Game Learning Analytics: Learning Analytics for Serious Games

Video games have become one of the largest entertainment industries, and their power to capture the attention of players worldwide soon prompted the idea of using games to improve education. However, these educational games, commonly referred to as serious games, face different challenges when brought into the classroom, ranging from pragmatic issues (e.g. a high development cost) to deeper educational issues, including a lack of understanding of how the students interact with the games and how the learning process actually occurs. This chapter explores the potential of data-driven approaches to improve the practical applicability of serious games. Existing work done by the entertainment and learning industries helps to build a conceptual model of the tasks required to analyze player interactions in serious games (gaming learning analytics or GLA). The chapter also describes the main ongoing initiatives to create reference GLA infrastructures and their connection to new emerging specifications from the educational technology field. Finally, it explores how this data-driven GLA will help in the development of a new generation of more effective educational games and new business models that will support their expansion. This results in additional ethical implications, which are discussed at the end of the chapter.

A reference business process for ecological niche modelling

Ecological niche modelling combines species occurrence points with environmental raster layers in order to obtain models for describing the probabilistic distribution of species. The process to generate an ecological niche model is complex. It requires dealing with a large amount of data, use of different software packages for data conversion, for model generation and for different types of processing and analyses, among other functionalities. A software platform that integrates all requirements under a single and seamless interface would be very helpful for users. Furthermore, since biodiversity modelling is constantly evolving, new requirements are constantly being added in terms of functions, algorithms and data formats. This evolution must be accompanied by any software intended to be used in this area. In this scenario, a Service-Oriented Architecture (SOA) is an appropriate choice for designing such systems. According to SOA best practices and methodologies, the design of a reference business process must be performed prior to the architecture definition. The purpose is to understand the complexities of the process (business process in this context refers to the ecological niche modelling problem) and to design an architecture able to offer a comprehensive solution, called a reference architecture, that can be further detailed when implementing specific systems. This paper presents a reference business process for ecological niche modelling, as part of a major work focused on the definition of a reference architecture based on SOA concepts that will be used to evolve the openModeller software package for species modelling. The basic steps that are performed while developing a model are described, highlighting important aspects, based on the knowledge of modelling experts. In order to illustrate the steps defined for the process, an experiment was developed, modelling the distribution of Ouratea spectabilis (Mart.) Engl. (Ochnaceae) using openModeller. As a consequence of the knowledge gained with this work, many desirable improvements on the modelling software packages have been identified and are presented. Also, a discussion on the potential for large-scale experimentation in ecological niche modelling is provided, highlighting opportunities for research. The results obtained are very important for those involved in the development of modelling tools and systems, for requirement analysis and to provide insight on new features and trends for this category of systems. They can also be very helpful for beginners in modelling research, who can use the process and the experiment example as a guide to this complex activity. (c) 2008 Elsevier B.V. All rights reserved.

On compliance of business processes with business contracts

This paper addresses the problem of ensuring compliance of business processes, implemented within and across organisational boundaries, with the constraints stated in related business contracts. In order to deal with the complexity of this problem we propose two solutions that allow for a systematic and increasingly automated support for addressing two specific compliance issues. One solution provides a set of guidelines for progressively transforming contract conditions into business processes that are consistent with contract conditions thus avoiding violation of the rules in contract. Another solution compares rules in business contracts and rules in business processes to check for possible inconsistencies. Both approaches rely on a computer interpretable representation of contract conditions that embodies contract semantics. This semantics is described in terms of a logic based formalism allowing for the description of obligations, prohibitions, permissions and violations conditions in contracts. This semantics was based on an analysis of typical building blocks of many commercial, financial and government contracts. The study proved that our contract formalism provides a good foundation for describing key types of conditions in contracts, and has also given several insights into valuable transformation techniques and formalisms needed to establish better alignment between these two, traditionally separate areas of research and endeavour. The study also revealed a number of new areas of research, some of which we intend to address in near future.

Major Issues in Business Process Management: An Expert Perspective

The results presented in this report form a part of a larger global study on the major issues in BPM. Only one part of the larger study is reported here, viz. interviews with BPM experts. Interviews of BPM tool vendors together with focus groups involving user organizations, are continuing in parallel and will set the groundwork for the identification of BPM issues on a global scale via a survey (including a Delphi study). Through this multi-method approach, we identify four distinct sets of outcomes. First, as is the focus of this report, we identify the BPM issues as perceived by BPM experts. Second, the research design allows us to gain insight into the opinions of organisations deploying BPM solutions. Third, an understanding of organizations’ misconceptions of BPM technologies, as confronted by BPM tool vendors is obtained. Last, we seek to gain an understanding of BPM issues on a global scale, together with knowledge of matters of concern. This final outcome is aimed to produce an industry driven research agenda which will inform practitioners and in particular, the research community world-wide on issues and challenges that are prevalent or emerging in BPM and related areas.

Modeling control objectives for business process compliance

Business process design is primarily driven by process improvement objectives. However, the role of control objectives stemming from regulations and standards is becoming increasingly important for businesses in light of recent events that led to some of the largest scandals in corporate history. As organizations strive to meet compliance agendas, there is an evident need to provide systematic approaches that assist in the understanding of the interplay between (often conflicting) business and control objectives during business process design. In this paper, our objective is twofold. We will firstly present a research agenda in the space of business process compliance, identifying major technical and organizational challenges. We then tackle a part of the overall problem space, which deals with the effective modeling of control objectives and subsequently their propagation onto business process models. Control objective modeling is proposed through a specialized modal logic based on normative systems theory, and the visualization of control objectives on business process models is achieved procedurally. The proposed approach is demonstrated in the context of a purchase-to-pay scenario.

Compliance aware business process design

Historically, business process design has been driven by business objectives, specifically process improvement. However this cannot come at the price of control objectives which stem from various legislative, standard and business partnership sources. Ensuring the compliance to regulations and industrial standards is an increasingly important issue in the design of business processes. In this paper, we advocate that control objectives should be addressed at an early stage, i.e., design time, so as to minimize the problems of runtime compliance checking and consequent violations and penalties. To this aim, we propose supporting mechanisms for business process designers. This paper specifically presents a support method which allows the process designer to quantitatively measure the compliance degree of a given process model against a set of control objectives. This will allow process designers to comparatively assess the compliance degree of their design as well as be better informed on the cost of non-compliance.