Database Design and Analysis (Term Paper Sample)

DATABASE DESIGN AND ANALYSIS
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Contents TOC \o "1-3" \h \z \u Section 1: Data Models PAGEREF _Toc388805342 \h 3a.Integration Data Models PAGEREF _Toc388805343 \h 3b.Application Data Models PAGEREF _Toc388805344 \h 3c.Business Requirement Data Models PAGEREF _Toc388805345 \h 4Section 2: Limitations and Benefits of Database Technologies PAGEREF _Toc388805346 \h 6Section 3: Example of Database Technologies PAGEREF _Toc388805347 \h 8a.Data Warehousing PAGEREF _Toc388805348 \h 8b.Data Mining PAGEREF _Toc388805349 \h 9c.Web Enabled Database Application PAGEREF _Toc388805350 \h 10d.Digital Libraries PAGEREF _Toc388805351 \h 10Section 4: Database Design Approaches PAGEREF _Toc388805352 \h 12a.Top-Down Approach to Database Design PAGEREF _Toc388805353 \h 12b.The Bottom-Up Approach to Database Design PAGEREF _Toc388805354 \h 12c.ERD modeling PAGEREF _Toc388805355 \h 12d.DFD modeling PAGEREF _Toc388805356 \h 12e.Normalization PAGEREF _Toc388805357 \h 13Section 5: Significance of Query Tools PAGEREF _Toc388805358 \h 14
Section 1: Data Models
* Integration Data Models
Integration data models refer to the models that incorporate many different applications. The integration of separate applications means the models are always instantiable. The scope of the model can be the all the data in the applications it incorporates or any data shared between two or more of these applications. Integration data models can also be used to share data between many enterprises. An example of integration models is the Enterprise Data Model (Simsion, 1994).
Advantages
* Comparison is made easier due to sharing of data
* Communication and exchange of information between firms is made easier, especially between a firm and its suppliers
* Data that should be held has restrictions and is not easily shared
Disadvantages
* There is difficulty in maintaining and supporting the models
* There is need to always rebuild the database each time there is a change in data exchange protocol
* Accessing and updating the models require a lot of procedure
* Application Data Models
These refer to data models that relate to a specific application (Simsion, 1994). Examples of application data models include Physical Data Model, Logical Data Model, Conceptual Data Model, and Canonical Data Model (Simsion, 1994). The model is generally a concept of database that represents application entities, the attributes of the entity, and the relations of the entity that are persisted in the schema of the database.
Advantages
* Helps in providing systematic information regarding a project in the firm
* Groups employees so that the supervisors and managers have an easy time in identifying the subordinates according to their skills and experience.
* Provide a link for interaction between the employees of a given department
Disadvantages
* Information relating to the skills of the employees as well as the skills required for the projects are unidirectional, making it hard for a given employee to determine the employees they can consult in the absence of the managers
* Information relation to changes in a project is unidirectional as only the managers or supervisors get such information.
* Business Requirement Data Models
This model is mainly developed to help in the reflection and capturing the business requirements statement. Making the notion simple and easily understandable during the creation of the model is very significant for the successful use of the model. The fact that this type of data model is developed to form the base for further analysis makes it necessary that it just captures a few necessary details. The model can also be used as an important framework for displaying the rules of the business as a way of defining the types of entity (Simsion, 1994).
Advantages
* Helps in defining the structure of the organization
* Define the business rules to the employees
Disadvantages
* Cannot help a firm interact with another
* Does not offers interaction between employees
When comparison and contrast is done among these groups of data models it is noticeable that the differences that exist is the area the data models target with regard to the organizational activities and the differences in the design of the models to meet their desired functions. On the other hand it is noticeable that the data models have the similarities in the benefits they bring to the organization. All the data models help in improving the quality of data, the definition of the requirements of the business, reuse of assets, reduction of data movement, reduction in the data movement, and reduction in maintenance in the firm.
Section 2: Limitations and Benefits of Database Technologies
The Advantages
* Controlling Data Redundancy: Ensures that all the data within the organization are created in one database and the problem of duplicate copies of data is eradicated.
* Data Consistency: Data is easily updated whenever changes occur and thus the consistency is ensured.
* Data Sharing: the data in the databases can be shared by as many users as possible provided that they are authorized to access the data. This eases the transfer of data in an organization.
* Data Integration: Data is store in tables within the database and there is the possibility to create relationships among the tables.
* Integrity Constraints: databases are fit with consistency and integrity constraints rules that ensure that only the correct data is entered in the database all the time.
* Data Security: the data in the systems is always protected in a way that it can only be accessed by authorized users of the systems.
Disadvantages
* Cost of Hardware & Software: upgrading both the hardware and the software may be costly as there is a requirement for a data processing of high speed and large memory size.
* Cost of Conversion: the data stored in the data files of any system that is computer based must always be converted to the files of the database when a database system replaces the file-based computer system. This process is always difficult and consumes a lot of time.
* Cost of Training Staff: application programmers and database administrators and other personnel who are concerned with handling of the system are expensive to train and compensate.
* Technical Staff Appointment: It may be expensive and cumbersome to come up with the right staff to manage the systems. It means the company will always hire qualified people who may be expensive to compensate.
* Database Failures: all the data is always integrated into one database and any failures due to corruption of the system may lead to lose of some data.
Section 3: Example of Database Technologies
* Data Warehousing
Data warehousing refers to database that is used in data analysis and reporting (Teory, 1994). The integration of data from one or many different sources makes a central storehouse of data referred to as data warehouse. The major role of the data warehouse is the storage of historical and current data that the management of an organization uses to create quarterly and annual reports.
Benefits of Data Warehouse
* Consistent presentation of the organization’s information
* Ensure that the data that it restructures make sense to the business users
* Makes is easy to come up with the decision-support queries for an organization
* Provides a single model for all the data of interest to the organization, regardless of the source of the data.
* Improves the quality of the data through the provision of consistent codes and description as well as flagging and fixing bad data.
Limitations
* Integration of data in a single system may lead to lose of some information when the system becomes corrupt
* The process of loading data from different operational system to the data warehouse is complicated especially when integrity has to be maintained.
* There is difficulty in the modification of the data warehouse to meet the needs of an organization that uses different approaches in handling their businesses.
* Data Mining
Data mining refers to a process of conceptually discovering the patterns that exist in large sets of data through methods of the intersections of machine learning, artificial intelligence, database systems and statistics (Teory, 1994). Data mining has the major goal of extracting the desired information from a set of data and transforming it to a structure that can be easily understood and hence the ease to further use the data.
Benefits
* Useful in marketing and retail for carrying out market analysis and coming up with the best market segment and entry strategies
* It provide financial institutions with information regarding loan repayments and credit reporting
* Helps in the detection of faulty equipment and determination of control parameters in manufacturing industries.
* Detection of criminal activities and money laundering as well as analysis of the records of financial transactions is achieved by governments through data mining.
Disadvantages
* It violates the need for privacy as its widespread makes it easy to get information that may be needed about any given person
* Security is an issue too with data mining as one is able to hack into other peoples accounts and still private information that may lead to lose of wealth or lives
* The information that is collected for ethical use may be used unethically by other people with ill motives like business gains or discrimination.
* Web Enabled Database Application
Web enabled Database refers to database applications that are placed within the interface of the web (Teory, 1994). The web designers design the websites as the database designers make the databases. The two...