ABSTRACT
GERGELY BABOS PH.D. PAPER
DEFINITION AND UTILIZATION OF META DATA STRUCTURE
IN INTEGRATED BUSINESS ENVIRONMENTS
There are three different philosophies to integrate IT systems. The differences are in data
management, storage and detailness. The method for widest, most complete and consolidated
storing of source system data is the data warehousing that focuses on fulfilling the most
complex analysis requirements. The middleware technology does not take care of data
storing, but knows exactly where to find a data in the source systems. To fulfill the data
supply requirements the relevant source data are selected online from the source system
databases. The enterprise resource planning systems collect a predefined, limited data set that
is necessary for their functionallities, but not for the fulfillment of all future data supply
requirements.
The IT system integration projects are continuously changing because of their size and
structure. The business environment, the changing processes and the arising requirements
modify both the operation and the data content of the source systems. The effect of the
modification of source systems is multiplied in the integration activities. The structure of
integrated database changes continuously because on the one hand the loading of a new
source systems modify the optimal database structure, on the other hand the source system
modifications triggers continuous change in integration process in order to keep the data
consistency in history. The business requirements are also continuously changing according to
the market environment. On the one hand new processes are to be implemented, on the other
hand the existing processes are to be modified.
The integration solutions integrate data. Both their actual state and their changes can be
represented by the screenshot and the modifications of their data. Data can be described by
meta data. I regarded both the screenshot (static time) and the modification (dynamic
characteristic) of data from three aspects using meta data. The three aspects are: the physical
characteristics of a data, the content and the business meaning of a data and the management
of data modifications. The introduced models representing the three aspects ensures to get a
complete picture of the actual state and content of our system and to be able to manage the
modifications, to create a structure for the modifying system that system operates regularly
during the period of modification. Using this description we can fulfill or requirement for
building a system environment where changes can be handled in a structured manner.
Changes and the new, or modifying requirements mean continuous development and
implementation tasks. This is the reason why an IT system integration project does not have a
target like delivering the implemented objects, but to deliver an environment, where the
handling and implementation of continuous modifications and new requirements can be
fulfilled effectively. Therefore the complex IT system integration project does not operate like
a real project in an organization, but like a department of the organization, however it keeps
its project characteristics on a high level. This is a project operations structure where the
complex IT system integration model is like an incremental structure, but the number of
increments is extremely high while the sub-projects are classical waterfall, or prototype
development projects.
I introduced the three meta data sets in models. These models are called complete meta data
models. The complete models are developed by own best practices and using literature. The
key points in the physical meta data model are the loading reports and the change
management that support business analysis. The business meta data models are results of own
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ABSTRACT
GERGELY BABOS PH.D. PAPER
improvement, the general opinion is that this is a hardly manageable field of IT system
integration. The main idea behind the business meta data model is the realization of
connection between different business concepts and their representation in data. The
connection is made by definitions that enable the representation of synonyms. This model is
the basis of several analysis and optimizations, I have implemented multiple applications
using this model that is introduced in the paper. In the implementation of the model
describing the project related characteristics we need to distinguish between operative
management and high level planning. The reason of separation is the continuous changing,
since the modification of a single element of a complex integrated IT system can effect the
operation of the whole system, so it is important to ensure a framework for the elastic
management of related development tasks.
The complete meta data models are final targets of the meta data management of a
development and implementation project, however there is no existing meta data management
system in practice that applies each functionality in a single application. The reason is on the
one hand can be found in history, because the system development and implementation
projects are in continuous time and resource pressure therefore the most important meta data
management functionallities can be implemented, on the other hand in the lack of conscious
meta data management during development. Usually the focus is on physical meta data
management. Bu the improving quality of business requirement fulfillment leads to a
convergence in meta data management, applications and analysis are developed that target a
complete meta data structure.
In the paper I introduce applications using entities of the complete meta data model
implemented in different IT system integration projects. The solutions according to the
applied meta data types are as follows:

Applications using the physical meta data model:
o Data quality monitoring application

Applications using the business meta data model:
o Mapping applications
o Reverse mapping application
o Data dictionary
o Application describing data definition according to complete meta data model

Applications using project management meta data:
o Workflow management application
o Change request management application
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