Databases, Retrieval and Storage Essay
This essays will address:
Evaluate how the design of a database can affect data quality
Discuss the role of a data dictionary in ensuring both the quality of enterprise-wide
data and data within a specific database application
Discuss how to ensure the integrity and security of data within a database
Explain the concept of data warehousing and how it is applicable to decision support.
Formulate a secure storage and retrieval process for healthcare data. Essay must be APA format, with 6 references, base on the following outline.
Databases
Data dictionaries, data mining, and data warehouses
Characteristics of data quality
Electronic healthcare information applications
Clinical information systems
 How Design of a Database Can Affect Data Quality
When designing a database, there are many factors that affect the quality of data as well as the way it is accessible and controllable. Documentation is very important when designing a database. Documentation helps in keeping a written record about the function of these systems. Documentation can either be incomplete, inaccurate or missing. All the three may lead to a loss of very important information which may not be retrieved using any method whatsoever (Narayan, 1988). This means that the data stored in the database may be affected especially if it cannot be retrieved using the required method and also affects the capturing of data.
Role of Data Dictionary
A data dictionary is designed for the purpose of having a collection or description of the data items for the use of programmers or other people that may use it. The data dictionary is very important in ensuring the quality of data in a specific data base application as well as enterprise-wide data (Gray, 1998). In order to maintain the quality of this data, the data dictionary plays the role of analysing and specifying information used in the creation of an enterprise model. The analysed and specified information is then used to create a data specification that is independent making a final logical database design. The data dictionary which provides information on both data and processes can also be used to provide views of data in making up the database design workbench.
Other than that, the data dictionary is also an accurate and consistent technique in communicating common meanings in a database (Kreines, 2003). By doing so, the meanings of all the elements remain constant and nobody has the ability to make any adjustment. This is made possible by documentation which acts as a reference for any analyst or user of the database. When all this is done, it is possible to locate and correct errors or omissions that may be made in the database. It is also possible to get a directive on how to deal with such cases.
How to Ensure Security and Integrity of Data in a Database
Data integrity which is sometimes referred to as data quality is the accuracy and consistency of data in a database while data security is the protection of data within a data base. In order to ensure that data security and integrity is upheld, there are a number of measures that should be taken up (Harrington, 2009). Since most databases are network capable, it is important that the precautions be based on this factor. The network administrator should be cautious when allowing accessibility to the database especially in controlling the different levels of security. Other than that, the directory used in sharing application of the database should be kept and used in confidentiality to ensure that there are no unauthorised users. Another method used to protect a database from unauthorised users is the use of data validation which prevents data corruption or effect of malicious software. It is also important to have backup for the data stored in the data base in case of an interruption that is hard to deal with (Rob, 2009). Data backup stores data in another location hence the data will not be entirely lost if it is lost in the initial system.
Data Warehousing and Application in Decision Support
Data warehousing is simply the combination of many databases across an enterprise providing a single and informative source of information. This helps in having a consolidated source of data from several sources. They provide business intelligence based on the fact that they have analytical tools and parts that help in running the required data. Business intelligence has been synonymous to decision support (Westerman, 2001). A decision support system is one which is designed for users in facilitating analysis of data on their own. Initially, data warehousing involved the use of tailor made queries that would help in retrieval on specific data from the databases which would then be compiled on a spreadsheet. This may be the relation between decision support systems and warehousing since the most commonly used decision support tool is the spreadsheet.
Secure Storage and Retrieval of Healthcare Data
Healthcare information and data is one of the most private things of an individual hence the need to have a secure and reliable way of keeping this data. In order to ensure that storage and retrieval of data is efficient it is important to put into consideration factors like privacy and accessibility. In storage, the data can be made private by having a validation code for accessing the data. The codes should be private and if violated, the system will not allow access until the system administrator is contacted. Other than that, retrieval should not be so easy such that unauthorised personnel can access the data. The network administrator should ensure that the data is not retrievable using malicious software or corruption of the system. The backup locations should also use the same methods in the storage of backup data. The system should also be upgradable especially if it is compatible with the network.
References
Gray, P., & Watson, H. J. (1998). Decision Support in the Data Warehouse. Upper Saddle River, N.J: Prentice Hall PTR.
Harrington, J. L., & Harrington, J. L. (2009). Relational Database Design And Implementation: Clearly Explained. Amsterdam: Morgan Kaufmann/Elsevier.
Kreines, D. C. (2003). Oracle Data Dictionary Pocket Reference. Sebastopol, CA: O’Reilly.
Narayan, R. (1988). Data dictionary: Implementation, use, and Maintenance. Englewood Cliffs, N.J: Prentice Hall.
Rob, P., & Coronel, C. (2009). Database Systems: Design, Implementation, and Management. Boston, Mass: Course Technology.
Westerman, P. (2001). Data Warehousing: Using the Wal-Mart Model. San Francisco, CA: Morgan Kaufmann.

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