Formal design of data warehouse and OLAP systems : a dissertation presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Information Systems at Massey University, Palmerston North, New Zealand

A data warehouse is a single data store, where data from multiple data sources is integrated for online business analytical processing (OLAP) of an entire organisation. The rationale being single and integrated is to ensure a consistent view of the organisational business performance independent from different angels of business perspectives. Due to its wide coverage of subjects, data warehouse design is a highly complex, lengthy and error-prone process. Furthermore, the business analytical tasks change over time, which results in changes in the requirements for the OLAP systems. Thus, data warehouse and OLAP systems are rather dynamic and the design process is continuous. In this thesis, we propose a method that is integrated, formal and application-tailored to overcome the complexity problem, deal with the system dynamics, improve the quality of the system and the chance of success. Our method comprises three important parts: the general ASMs method with types, the application tailored design framework for data warehouse and OLAP, and the schema integration method with a set of provably correct refinement rules. By using the ASM method, we are able to model both data and operations in a uniform conceptual framework, which enables us to design an integrated approach for data warehouse and OLAP design. The freedom given by the ASM method allows us to model the system at an abstract level that is easy to understand for both users and designers. More specifically, the language allows us to use the terms from the user domain not biased by the terms used in computer systems. The pseudo-code like transition rules, which gives the simplest form of operational semantics in ASMs, give the closeness to programming languages for designers to understand. Furthermore, these rules are rooted in mathematics to assist in improving the quality of the system design. By extending the ASMs with types, the modelling language is tailored for data warehouse with the terms that are well developed for data-intensive applications, which makes it easy to model the schema evolution as refinements in the dynamic data warehouse design. By providing the application-tailored design framework, we break down the design complexity by business processes (also called subjects in data warehousing) and design concerns. By designing the data warehouse by subjects, our method resembles Kimball's "bottom-up" approach. However, with the schema integration method, our method resolves the stovepipe issue of the approach. By building up a data warehouse iteratively in an integrated framework, our method not only results in an integrated data warehouse, but also resolves the issues of complexity and delayed ROI (Return On Investment) in Inmon's "top-down" approach. By dealing with the user change requests in the same way as new subjects, and modelling data and operations explicitly in a three-tier architecture, namely the data sources, the data warehouse and the OLAP (online Analytical Processing), our method facilitates dynamic design with system integrity. By introducing a notion of refinement specific to schema evolution, namely schema refinement, for capturing the notion of schema dominance in schema integration, we are able to build a set of correctness-proven refinement rules. By providing the set of refinement rules, we simplify the designers's work in correctness design verification. Nevertheless, we do not aim for a complete set due to the fact that there are many different ways for schema integration, and neither a prescribed way of integration to allow designer favored design. Furthermore, given its °exibility in the process, our method can be extended for new emerging design issues easily

Fusion of Information and Analytics: A Discussion on Potential Methods to Cope with Uncertainty in Complex Environments (Big Data and IoT)

International audienceInformation overload and complexity are core problems to most organizations of today. The advances in networking capabilities have created the conditions of complexity by enabling richer, real-time interactions between and among individuals, objects, systems and organizations. Fusion of Information and Analytics Technologies (FIAT) are key enablers for the design of current and future decision support systems to support prognosis, diagnosis, and prescriptive tasks in such complex environments. Hundreds of methods and technologies exist, and several books have been dedicated to either analytics or information fusion so far. However, very few have discussed the methodological aspects and the need of integrating frameworks for these techniques coming from multiple disciplines. This paper presents a discussion of potential integrating frameworks as well as the development of a computational model to evolve FIAT-based systems capable of meeting the challenges of complex environments such as in Big Data and Internet of Things (IoT)

Business process modelling in small- to medium-sized enterprises

Data flow analysis is used in a novel context for business process modelling. A framework is presented together with its enterprise modelling concepts and the associated modelling tools. The framework was specifically developed for small- to medium-sized industries. The strengths and weaknesses of the general data flow analysis approach are discussed in terms of its suitability for Hong Kong's small- to medium-sized industries. A case example is also presented to illustrate the methodology.published_or_final_versio

S-BPM in the Wild

This is the first book to present field studies on the application of subject-oriented business process management (S-BPM). Each case presents a specific story and focuses on an essential modeling or implementation issue, and most end with implications or suggestions for further studies. Significant variables and success factors are identified that were discovered during the respective study and lead to suggesting S-BPM novelties. For each case, the authors explain step-by-step how the story develops, and provide readers guidance by detailing the respective rationale. The studies covered are clustered according to three main S-BPM themes: Part I “Business Operation Support” documents approaches to the practical development of S-BPM solutions in various application domains and organizational settings, while Part II “Consultancy and Education Support” highlights cases that can help to train readers in S-BPM modeling and knowledge acquisition for S-BPM lifecycle iterations. It also refers to architecting S-BPM solutions for application cases based on hands-on experience. Part III “Technical Execution Support” focuses on concepts for utilizing specific theories and technologies to execute S-BPM models. It also addresses how to create reference models for certain settings in the field. Lastly, the appendix covers all relevant aspects needed to grasp S-BPM modeling and apply it based on fundamental examples. Its format reconciles semantic precision with syntactic rigor.>Addressing the needs of developers, educators and practitioners, this book will help companies to learn from the experiences of first-time users and to develop systems that fit their business processes, explaining the latest key methodological and technological S-BPM developments in the fields of training, research and application

Requirements specification using concrete scenarios

The precision of formal specifications allows us to prove program correctness. Even if formal methods are not used throughout the software project, formalisation improves our understanding of the problem. Formal specifications are amenable to automated analysis and consistency checking. However using them is challenging. Customers do not understand formal notations. Specifiers have difficulty tackling large problems. Once systems are built, formal specifications quickly become outdated during software maintenance. A method of developing formal specifications using concrete scenarios is proposed to tackle the disadvantages just mentioned. A concrete scenario describes system behaviour with successive steps. The pre- and post-states of scenario steps are expressed with actual data rather than variables. Concrete scenarios are expressed in a natural language or formal notation. They increase customer involvement in the creation of formal specifications. Scenarios may be ranked by priorities allowing specifiers to focus on a small part of the system. Formal specifications are constructed incrementally. New requirements are also captured in concrete scenarios which guide the modification of formal specifications. On one hand, concrete scenarios assist the creation and maintenance of formal specifications. On the other hand, they facilitate program correctness proofs without using conventional formal specifications. This is achieved by adding implementation details to customer scenarios. The resulting developer scenarios, encapsulating decisions of data structures and algorithms, are generalised to operation schemas. With the implementation details, the schemas written in formal notations are programs rather than specifications.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Subject-Oriented Business Process Management

Information Systems Applications (incl.Internet); Business Information Systems; Computer Appl. in Administrative Data Processing; Management of Computing and Information System