Change Management in Large-Scale Enterprise Information Systems

Abstract. The information infrastructure in today’s businesses consists of many interoperating autonomous systems. Changes to a single system can therefore have an unexpected impact on other, dependent systems. In our Caro approach we try to cope with this problem by observing each system participating in the infrastructure and analyzing the impact of any change that occurs. The analysis process is driven by declaratively defined rules and works with a generic and ex-tensible graph model to represent the relevant metadata that is subject to changes. This makes Caro applicable to heterogeneous scenarios and customizable to spe-cial needs.

BUILDING DSS USING KNOWLEDGE DISCOVERY IN DATABASE APPLIED TO ADMISSION & REGISTRATION FUNCTIONS

This research investigates the practical issues surrounding the development and implementation of Decision Support Systems (DSS). The research describes the traditional development approaches analyzing their drawbacks and introduces a new DSS development methodology. The proposed DSS methodology is based upon four modules; needs' analysis, data warehouse (DW), knowledge discovery in database (KDD), and a DSS module. The proposed DSS methodology is applied to and evaluated using the admission and registration functions in Egyptian Universities. The research investigates the organizational requirements that are required to underpin these functions in Egyptian Universities. These requirements have been identified following an in-depth survey of the recruitment process in the Egyptian Universities. This survey employed a multi-part admission and registration DSS questionnaire (ARDSSQ) to identify the required data sources together with the likely users and their information needs. The questionnaire was sent to senior managers within the Egyptian Universities (both private and government) with responsibility for student recruitment, in particular admission and registration. Further, access to a large database has allowed the evaluation of the practical suitability of using a data warehouse structure and knowledge management tools within the decision making framework. 1600 students' records have been analyzed to explore the KDD process, and another 2000 records have been used to build and test the data mining techniques within the KDD process. Moreover, the research has analyzed the key characteristics of data warehouses and explored the advantages and disadvantages of such data structures. This evaluation has been used to build a data warehouse for the Egyptian Universities that handle their admission and registration related archival data. The decision makers' potential benefits of the data warehouse within the student recruitment process will be explored. The design of the proposed admission and registration DSS (ARDSS) will be developed and tested using Cool: Gen (5.0) CASE tools by Computer Associates (CA), connected to a MSSQL Server (6.5), in a Windows NT (4.0) environment. Crystal Reports (4.6) by Seagate will be used as a report generation tool. CLUST AN Graphics (5.0) by CLUST AN software will also be used as a clustering package. Finally, the contribution of this research is found in the following areas: A new DSS development methodology; The development and validation of a new research questionnaire (i.e. ARDSSQ); The development of the admission and registration data warehouse; The evaluation and use of cluster analysis proximities and techniques in the KDD process to find knowledge in the students' records; And the development of the ARDSS software that encompasses the advantages of the KDD and DW and submitting these advantages to the senior admission and registration managers in the Egyptian Universities. The ARDSS software could be adjusted for usage in different countries for the same purpose, it is also scalable to handle new decision situations and can be integrated with other systems

METADATA REPOSITORY MODEL FOR DATA WAREHOUSE SCHEMA EVOLUTION AND INTEGRATION WITH MASTER DATA MANAGEMENT SYSTEM

Skladište podataka (SP) se u današnje vrijeme nalazi u iznimno dinamičnom poslovnom okruženju. S jedne strane imamo brojne (heterogene) izvore podataka koji su podložni čestim promjenama podataka i strukture, dok s druge strane imamo brojne promjene u informacijskim zahtjevima koje postavljaju poslovni korisnici. Višedimenzionalna shema (VDS) u svakom trenutku mora moći usvojiti promjene iz izvora podataka te im se prilagoditi, kao i zadovoljiti korisničke zahtjeve za informacijama, što je iznimno složen zadatak. Problem koji se istražuje kod evolucije skladišta podataka jest pamćenje promjena opsega te strukture podataka i meta-podataka, u dužem vremenskom periodu. Akademska zajednica je do danas napravila određene korake prema rješavanju ovoga problema, no uvijek ima prostora za poboljšanje postojećih istraživanja, kao i za osmišljanje novih rješenja. Cilj ovog doktorskog istraživanja bio je razviti model repozitorija meta-podataka (MDV) koji se zasniva na Data Vault (DV) metodi za modeliranje baza podataka. Ovako definiran repozitorij meta-podataka služi za integraciju skladišta podataka (SP) i sustava za upravljanje matičnim podacima (UMP) te za praćenje i upravljanje promjenama u SP/UMP podacima i meta-podacima, kao i u njihovim shemama. Na ovaj način evolucija sheme skladišta podataka provodi se isključivo uz proširenje postojeće sheme i bez gubitka informacija. Također, složenost provedbe evolucije SP/UMP sheme je smanjena u odnosu na tradicionalne pristupe zasnovane na relacijskom modelu, a repozitorij zasnovan na MDV modelu služi kao proširenje tradicionalnog relacijskog sistemskog kataloga. U svrhu izgradnje praktičnog prototipa i testiranja predloženog rješenja razvijen je trajni i obuhvatni model repozitorija meta-podataka za integraciju i praćenje promjena shema SP i UMP, sistematiziran je formalni konačni skup osnovnih promjena nad shemom SP i UMP, definirana je formalna algebra za održavanje SP i UMP sheme te je razvijena arhitektura integriranog SP i UMP. Na kraju je razvijen i sam praktični prototip koji služi za empirijsku verifikaciju predloženog rješenja.Data Warehouse (DW) environment nowadays is an extremely dynamic one. On the one hand we have a number of (heterogeneous) data sources that are subject to frequent changes of data and structure, while on the other hand we have the frequent changes in the information requirements (set by business users). DW has an extremely complex task it must at all times be able to adapt to changes from data sources as well as to satisfy user's requests for information. This problem that we explore here is known and recognized in literature as a DW evolution problem tracking and storing the scope and structure changes of data and metadata for a very long time period. The academic community has taken some steps towards solving this problem but there is always some room for an improvement of the existing research, as well as for a development of new solutions. The goal of this doctoral thesis was to develop a metadata repository model (MDV) which is based on the Data Vault (DV) method for database modeling. Thus defined metadata repository model is used for integrating a data warehouse (DW) system and a master data management (MDM) system and for tracking and managing changes in the DW/MDM data and metadata, as well as in their schemas. In this way, a DW schema evolution is carried out only with the expansion of the existing schema and without loss of information. Also, the complexity of the DW schema evolution implementation is decreased compared to traditional approaches based on the relational model. Additionally, MDV repository serves as an extension of traditional relational database system catalog. In order to build a practical prototype and to test the proposed solution, a permanent and comprehensive metadata repository model for integration and tracking of DW/MDM data and schema changes was developed, a final set of fundamental changes over the DW/MDM schema was systematized, a formal algebra for DW/MDM schema maintenance was develped, an architecture of integrated DW/MDM was proposed, and a prototype of our dual DW/MDM solution was developed and empirically verifie