Tugas I
Kuliah Sistem Basis Data 2
Dosen : Caca E. Supriana, S.Si., MT.
Teknik Informatika Universitas Pasundan
2015
Data
Model Defined
Data
modeling is an integral part of the process of designing and developing a data
system. While designing and developing a data system for an organization, you
take into account all the information that would be needed to support the various
business processes of the organization.
What Is
a Data Model ?
A data
model is a device that :
Helps
the users or stakeholders understand clearly the database system that is being implemented
based on the information requiremen ts of an organization. Enables
the database practitioners to implement the database system exactly conforming
to the information requirements.
A data
model, therefore, serves as a critical tool for communication with the users;
it also serves as a blueprint of the database system for the developers. Data
modeling is a technique for exploring the data structures needed to support an organization.
A data model must record and indicate the content, shape, size, and rules of
the data elements used throughout the scope of the various business processes
of the organization.
Data
Life Cycle
A data
model acts as a bridge from real world information to database storing relevant
data content. Data Life Cycle, follow the stages that data goes through in an
organization. First, a need for data arises to perform the various business
processes of an organization. Then a determination is made about exactly what
data is needed. Gathering of the data takes place. Then the data gets stored in
the database system. In the next stage, data is manipulated by reading it from
storage, combining it in various desired ways, and changing it. After a while
some of the data gets archived and stored elsewhere. After some of the data
completes its usefulness, the corresponding data elements get deleted from the
database system.
·
Needing Data. In this earliest stage, an
organization recognizes the need for data for performing the various business
processes.
·
Determining Needed Data. Once you recognize the
need for data, you have to determine which data elements are needed for
performing business processes.
·
Gathering Needed Data. After the determination
of which data is needed, collection of data takes place. Here you apply a sort
of filter to gather only the data that is needed and ignore the irrelevant data
that is not necessary for any of your business processes.
·
Storing Data. The collected data must be stored
in the database using appropriate methods of storage.
·
Using Data. Data, collected and stored, is
meant for usage. That is the ultimate goal in the data life cycle. At this
stage, you will combine various data elements, retrieve data elements for
usage, modify and store modified data , and add new data created during the
business processes. At this stage, the data model acts as a directory and map
to direct the ways of combining and using data.
·
Deleting Obsolete Data. After a while, a
particular data element in storage may become stale and obsolete. After a
period of time, the data element may no longer be useful and therefore, not
accessed in any transactions at all.
Archiving Historical Data. However, some data elements may still be
useful even long after any activity on those data elements had ceased.
Who
Performs Data Modeling ?
Data
modeling specialists with appropriate training, knowledge, and skills do the
work of data modeling. A data modeler may be thought of performing the
following functions :
·
Scanning Current Details. The data modeler
scans and captures details of the current state of the data system of the
enterprise. New models are built by looking at the current data structures.
·
Designing the Architecture. The data modeler is
an architect designing the new data model. He or she puts together all the
pieces of the architecture.
·
Documenting and Maintaining Meta-Data. The data
modeler is like a librarian and custodian of the data about the data of the
organization. The data modeler is also a tremendous source of information about
the data structures and elements, current and proposed.
·
Providing Advice and Consultation. With
in-depth knowledge about the composition of the data system of an organization,
the data modeler is the expert for consultation.
Information Levels
A data
model must be at a high and general level that can be easily understood by the
users. This will help the communication with the users. At the same time, we understand
that the data model must also be detailed enough to serve as a blueprint. At
one level, the data model needs to be general; at another level, it has to be
detailed. What this means is that representation of information must be done at
different levels. The data model must fit into different information levels. In
practice, data models are created at different information levels to represent
information requirements.
·
Conceptual Level. This is the highest level
consisting of general ideas about the information content. At this level, you
have the description of application domain in terms of human concepts. This is
the level at which the users are able to understand the data system. This is a
stable information level. At this level, the data model portrays the base type
business objects, constraints on the objects, their characteristics, and any
derivation rules. The data model is independent of all physical
considerations.
·
External Level. The data model is comprehensive
and complete. Every piece of information required for every department and every
user group is depicted by the comprehensive conceptual model. However, when you
consider a particular user group, that group is not likely to be interested in
the entire conceptual model. A data model at the external level consists of
fragments of the entire conceptual model. In a way, each fragment is a
mini conceptual model.
·
Logical Level. At this level, the domain
concepts and their relationships are explored further. This level accommodates
more details about the information content. Still, storage and physical
considerations are not part of this level. Not even considerations of a
specific DBMS find a place at this level. However, representation is made based
on the type of database implementation — relational, hierarchical, network, and
so on.
Internal or Physical Level. This information level deals with the
implementation of the database on secondary storage. Considerations of storage
management, access management, and database performance apply at this level.
Here intricate and complex details of the particular database are relevant. The
intricacies of the particular DBMS are taken into account at the physical
level. The physical data model represents the details of implementation.
Source :
Data
Modeling Fundamentals : A Practical Guide for IT Professionals, Paulraj
Ponniah, Wiley-Interscience, 2007
Tugas :
1. Baca dan pahami.
2. Terjemahkan ke dalam Bhs. Indonesia dan rangkumlah.
3. Tulis rangkuman menggunakan ballpoint dalam kertas A4 maks. 2 lembar.
4. Tulis Nama, NRP dan tanda tangan mhs. pada awal rangkuman.
5. Dikumpulkan pada pertemuan berikutnya, terlambat mengumpulkan tidak akan dinilai !
Selamat bekerja !
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