Adaptation of Hitachi Solutions Europe intellectual property for Dynamics 365 Project Operations

Microsoft Dynamics 365 Finance & Operations is one of the services that Hitachi Solutions Europe uses. It is a multi-company, multi-language and multi-currency enterprise resource planning (ERP) system by Microsoft that allows for organizations to be digitally transformed and enables them to monitor the performance of each company in real time, forecast results, and make data driven decisions to boost the growth of a company, regardless of its size and the industry in which it operates. However, recently, Microsoft has planned to expand Finance & Operations features to Project Operations, a recent Microsoft application for project management, and further develop that product. As a first step of that said migration, Microsoft has decided to split two different Finance & Operations modules’ (Project Management & Accounting (PMA) and Project Services Automation (PSA)) features between Finance & Operations and Project Operations. Regarding Finance & Operations, it is used as a foothold in the Hitachi Essentials for Professional Services Intellectual Property, which is one of the many IP’s of Hitachi Solutions Europe. As such, it had to be updated properly in order to keep on fulfiling most of its previously established requirements and implement new ones according to the new out-ofbox Microsoft logic that came with the recent product release. In the end, what was achieved was the adaptation of the Hitachi Essentials for Professional Services Intellectual Property with the new requirements implemented according to the Microsoft approach. To conclude, it is possible to infer that the work done in regards to both Finance & Operations and Project Operations managed to achieve all of the desired Hitachi custom features design, improving the user experience tied to these features.O Microsoft Dynamics 365 Finance & Operations é um dos serviços utilizados pela Hitachi Solutions Europe. Este consiste num sistema ERP da Microsoft utilizado por organizações que possibilita a gestão de atividades de negócio no dia-a-dia, que suporta diversas empresas, idiomas e moedas. Adicionalmente, Finance & Operations permite que organizações sejam digitalmente transformadas e que estas possam também monitorizar o desempenho de cada uma das suas empresas em tempo real, prever resultados e tomar decisões orientadas por dados de forma a impulsionar o seu crescimento independentemente da sua dimensão e da indústria em que operam. No entanto, recentemente, a Microsoft planeou a expansão de algumas funcionalidades de Finance & Operations para Project Operations, uma aplicação recentemente criada pela Microsoft para gestão de projetos, de forma a elevar o desenvolvimento da mesma. Numa fase inicial, a Microsoft decidiu dividir as funcionalidades de dois módulos diferentes relativos a Finance & Operations (Project Management & Accounting (PMA) e Project Services Automation (PSA)) entre Finance & Operations e Project Operations. No que diz respeito a Finance & Operations, esta serve de base para o Hitachi Essentials for Professional Services Intellectual Property, uma das muitas propriedades intelectuais (IP) da Hitachi Solutions Europe. Como tal, teve de ser devidamente atualizada de forma a continuar a cumprir os requisitos previamente estabelecidos e implementar novos de acordo com a nova lógica da Microsoft proveniente da mais recente versão do produto. De forma a compreender o processo de adaptação da plataforma IP às mudanças mais recentes da Microsoft, foi analisado o processo completo de criação de Project Operations e a influência que a existência de diferentes aplicações de negócios para projetos segregadas tiveram nessa decisão, o futuro da nova aplicação Project Operations e as diferenças que surgiram em FinOps comparativamente ao que existia previamente (tais como funcionalidade e esquemas de licenças). As tecnologias envolvidas no decorrer do projeto e possíveis alternativas foram descritas no Estado de Arte e classificadas de acordo com três categorias: aplicações de negócio, de colaboração ou técnicas. Estas foram também classificadas de acordo com um critério simbolizado pelo grau de conhecimento prévio que o autor possui sobre as tecnologias. Desta forma, de acordo com o critério de classificação previamente definido, foi possível detalhar quais das tecnologias em estudo eram do conhecimento do autor. No que se refere a possíveis alternativas ao trabalho efetuado, o autor tinha como possibilidades remover funcionalidades que deixaram de funcionar do sistema, remover tudo e tentar mover para Project Operations ou simplesmente adaptar as funcionalidades que deixaram de funcionar para Project Operations (decisão implementada). A análise de valor foi efetuada para estas alternativas, permitindo averiguar a melhor decisão foi a implementada. Relativamente ao design, o esquema de licença inicial bem como os esquemas de licenças implementados pela Microsoft foram detalhados. Contudo, de momento, não existem possíveis alternativas de design. Porém, no futuro, caso a Microsoft migre todo o conteúdo associado a Finance & Operations para Project Operations, tornar-se-á possível a adaptação da solução da Hitachi completa para Project Operations. A arquitetura base da Microsoft está inacessível para edições, consequentemente forçando a utilização de ferramentas compatíveis com a mesma. Posteriormente, o documento aborda os requisitos do trabalho, expondo as diferentes tarefas, pedidos de mudança e bugs pelos quais o autor foi responsável, classificando-os como funcionais ou não funcionais e providenciando as suas descrições. Aquando o término da secção de design, foi possível averiguar qual o processo técnico e modelo de customização da solução, a qual se baseou em extensibilidade de código. Adicionalmente, foi possível verificar o funcionamento da integração entre Finance & Operations e Project Operations através de um exemplo dos critérios de aceitação de um requisito e respetivo resultado final. De forma a avaliar a solução implementada foram utilizados os seguintes indicadores: um indicador relativo ao índice de aceitação dos requisitos implementados pelo autor; uma métrica referente à revisão da necessidade de esforço relativa à proporção da complexidade de requisitos. De forma a complementar os indicadores, foram levantadas as três hipóteses seguintes: validação do cumprimento de requisitos de acordo com os critérios predefinidos, bem como da entrega de valor; validação do cumprimento de requisitos de acordo com os critérios predefinidos, mas não da entrega de valor; incumprimento dos critérios de avaliação. Para tal, foi redigido um questionário ao tester responsável pela avaliação dos requisitos implementados, como também foi executado um modelo de avaliação de qualidade (Quality Evaluation Framework), os quais corroboram o sucesso do trabalho efetuado pelo autor. Finalmente, foi possível aferir que a adaptação do Hitachi Essentials for Professional Services Intellectual Property alinhada com a abordagem da Microsoft foi efetuada com sucesso. Desta forma, a propriedade intelectual da Hitachi foi atualizada, tendo compatibilidade tanto com Finance & Operations como Project Operations, mantendo o design personalizado pela Hitachi Solutions Europe

DEVELOPMENT OF DATABASE BASED FIELD TEST APPLICATION FOR INDUSTRY

The fast development of automation has led to many different dynamics of different applications. According to worldwide statistics, the number of smartphone users has grown exponentially which also persuaded software developers and engineers to make numerous mobile applications. Generally, field testing is only carried out when there is in need of collecting important data from individuals to figure out blunders and database technology allows storing all the information. In this work, a Microsoft based PowerApps application was created for a company. The requirements necessary for the application were given by the customer and in the process of making the application, any improvements which were obligatory were also specified by the client. I have had a chance to learn the complete PowerApps UI with the resources provided by the company I work for. Firstly, the concepts of a database have been introduced to give a general idea of how the Microsoft SQL Server is used for the entire project. Secondly, there is a discussion about how PowerApps is used and how unified the system is when connecting the database server. After that, I have discussed step by step of how the PowerApps application is sending the data to the database server when a user is using the mobile application. In short, the PowerApps application provides an easier field testing approach for the workers

An explanatory case study on cloud computing applications in the built environment

Fragmentation of practices is one of the key issues in the built environment. However, with advances in Information and Communication Technology (ICT), particularly cloud computing, the fragmentation of working practices can be potentially overcome. The technology could enhance communication and information flowin various stages along a project life cycle.Due to the increasing demands and the newly developed cloud computing applications, it is critical to review and identify the appropriate cloud computing applications in the built environment. A total of forty two cloud computing applications consisting of general cloud applications, Building Information Modelling (BIM), and project management cloud applications were selected and critically reviewed. A decision-making model was also developed to assist parties in selecting a suitable application. The explanatory case study has discovered numerous possible cloud computing applications in various disciplines, for example, Google Apps, Autodesk BIM 360, and Viewpoint are the applications with the most features. The findings contribute to creating a certain awareness and an insight to reduce the fragmented working practices in the built environment

Business model benchmarking : how a machine learning-based tool can support business model innovation

An increasing body of literature has developed around business models and business model innovation in recent years, establishing the concepts’ relevance for the competitiveness of a firm. The process of innovating a business model is less researched and still constitutes a com-plex and challenging task for businesses. Despite the advancements of technology, only few tools have been developed to support said process. Thus, present work focuses on how this process can be facilitated by introducing the concept of benchmarking and complementing it through a machine learning model. A machine learning supported multi-case theory building approach was followed to indicate how benchmarking business models might benefit compa-nies and to arrive at a machine learning model supporting this endeavour. The business models of 306 firms were evaluated to do so. Benchmarking business models can benefit a company by monitoring and learning from other organizations to spark innovation and support idea cre-ation. The machine learning model predicts business model patterns which are used to make processes across companies comparable. The present thesis results in a business model bench-marking tool which supports managers and entrepreneurs alike in their quest of business model innovation.Nos últimos anos, um número significativo de estudos foram desenvolvidos em torno de modelos de negócios e na inovação dos mesmos, afirmando a relevância destes conceitos para a competitividade de uma empresa. O processo de inovação de um modelo de negócio não só é pouco estudado, como ainda constitui uma tarefa complexa e desafiadora para as empresas. Apesar dos avanços da tecnologia, apenas algumas meios foram desenvolvidos para dar suporte ao referido processo. Assim, a presente dissertação realça como este processo pode ser facilitado, introduzindo o conceito de benchmarking e completando-o através do modelo ‘machine learning model’. Multi-case theory building foi apoiado pelo modelo ‘machine learning model’ para indicar como a análise de benchmark dos modelos de negócio podem beneficiar as empresas e para alcançar um machine learning model que suporte esse esforço. Nesse sentido, os modelos de negócio de 306 empresas foram avaliados. A aprendizagem e monitorização de outras organizações pode beneficiar o modelo de negócio de uma empresa, estimulando a inovação e a criação de novas ideias. Machine learning model é um modelo que prevê os padrões de modelos de negócio que são utilizados para tornar os processos entre empresas comparáveis. A presente dissertação desenvolveu um método de análise de benchmark de modelos de negócio que apoia gerentes e empreendedores na pesquisa pela inovação de modelos de negócio

Managing law practice technology

Presented by Barron K. Henley, at a seminar by the same name, held November 17, 2020

Digital transformation of financial management at the enterprise

The aim of the graduation work is to study theoretical knowledge in the field of corporate technologies in financial management of the enterprise; analyze the market of ERP systems; consider the necessary conditions for the implementation of the ERP system, as well as the difficulties that may arise when trying it. The object of the study - is information technology (IT) in the financial control system at the enterprise. The first section tells about the history of financial controlling, when it begun and how it was operating. Also, this part defines controlling tools and the place of controlling in the management system. The second section is about theory and practice of modern software in the field of financial management; analysis of the most popular ERP systems, their advantages and disadvantages and the efficiency of the investment budget in the implementation of IT, which is allocated for these purposes by enterprises. The third section analysis domestic and world experience in implementing ERP systems in financial management of the enterprise; defines alternative options of the ERP-system implementation at the enterprise on case study and shows economic efficiency of implantation of ERP-system, pros and cons of each project and also gives recommendations for improving information technology in financial management at the enterprise

INTEGRATION OF BLOCKCHAIN TECHNOLOGIES AND MACHINE LEARNING WITH DEEP ANALYSIS

The successful development of the digital economy, which we can observe since the advent of the internet, is closely related to progress in several "frontier technologies" (frontier technologies), among which the most important, according to the scientific community and international organizations, are such software-oriented technologies as blockchain, Big Data Analytics (Big Data), Artificial Intelligence (AI) and cloud Computing (Cloud Computing), as well as specialized machine-oriented equipment: 3D printers, internet of Things devices (Internet of things Things, IoT), automation and robotics. Significant progress in the application of these technologies contributes to the growth of production capabilities, labor productivity, and capital return of both digital companies and enterprises of the non-digital economy while transforming their established business models and principles of generating income and expenses of companies. This makes it necessary to study the above technologies in detail from the point of view of analyzing their essence, role, and potential for use in various spheres of economic life. Although the term "blockchain" has recently entered scientific and public use, the idea of the technology appeared in the late 1980s, namely in 1989. Lamport proposed "a model for achieving consensus on results in a network of computers, where computers or the network itself can be unreliable". In 2008, Satoshi Nakamoto proposed the concept of using a decentralized computer network to operate a P2P electronic money system. In the article "Bitcoin: a Peer-to-Peer Electronic Cash System" published on the internet, the innovator described the algorithm of functioning of the Bitcoin cryptocurrency as a completely independent electronic cash system from a single issue Center, which does not require the trust (mediation) of a third party, but relies on direct operations between the parties to the transaction, protected by cryptographic encryption

The Technological Emergence of AutoML: A Survey of Performant Software and Applications in the Context of Industry

With most technical fields, there exists a delay between fundamental academic research and practical industrial uptake. Whilst some sciences have robust and well-established processes for commercialisation, such as the pharmaceutical practice of regimented drug trials, other fields face transitory periods in which fundamental academic advancements diffuse gradually into the space of commerce and industry. For the still relatively young field of Automated/Autonomous Machine Learning (AutoML/AutonoML), that transitory period is under way, spurred on by a burgeoning interest from broader society. Yet, to date, little research has been undertaken to assess the current state of this dissemination and its uptake. Thus, this review makes two primary contributions to knowledge around this topic. Firstly, it provides the most up-to-date and comprehensive survey of existing AutoML tools, both open-source and commercial. Secondly, it motivates and outlines a framework for assessing whether an AutoML solution designed for real-world application is 'performant'; this framework extends beyond the limitations of typical academic criteria, considering a variety of stakeholder needs and the human-computer interactions required to service them. Thus, additionally supported by an extensive assessment and comparison of academic and commercial case-studies, this review evaluates mainstream engagement with AutoML in the early 2020s, identifying obstacles and opportunities for accelerating future uptake

Legal Technology for Senior Lawyers

Meeting proceedings of a seminar by the same name, held October 25, 202