Attached is some information that should be helpful and what I originally wrote but also attached is the grading rubric for reference that says what’s missing.
Unit Outcomes addressed in this Assignment:
Compare 2 data bases
- 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.
- Describe the purpose of healthcare data sets and standards used healthcare data collection.
- Identify different types of data sets and their purpose
Course Outcomes assessed in this Assignment:
- HI300-2: Classify database technologies and healthcare information systems used to manage data and information.
- PC 3.2: Interact with others in a professional manner using appropriate communication and presentation skills.
Please complete all parts in a Microsoft Word document.
- The body of your document should be at least 1000 words in length.
- Quoting should be less than 10% of the entire paper. Paraphrasing is necessary.
- Students must cite and reference at least 4 credible sources from the Library. APA style
Expert Solution Preview
In this assignment, we will be comparing two databases, evaluating the importance of database design in maintaining data quality, discussing the role of a data dictionary in ensuring data quality, and exploring ways to ensure data integrity and security. Moreover, we will be explaining the concept of data warehousing and its applicability in decision support, and describing the purpose of healthcare data sets and standards used in healthcare data collection.
To compare two databases, we need to first choose the databases to compare. After selecting the two databases, we need to evaluate their features, performance, scalability, and security. We can use various criteria to compare databases, such as database type, structure, data manipulation capabilities, indexing, and querying speed. We can also consider factors like ease of use, user interface, and installation and maintenance requirements. By comparing different databases, we can identify the strengths and weaknesses of each database and select the best one for a particular application.
The design of a database can significantly affect the quality of data stored in it. A well-designed database can ensure data accuracy, completeness, consistency, and validity. The database design should consider various factors like data requirements, data types, data relationships, data normalization, and indexing. Data relationships and normalization ensure that data is stored in the most efficient and effective way. Indexing can improve query performance and speed up data retrieval. By maintaining data quality, a database can ensure that the information stored in it is reliable and trustworthy.
A data dictionary is a critical tool for maintaining data quality within a database application. A data dictionary contains information about data elements used in the database, including data types, relationships, and constraints. It provides a common language for all users of the database, ensuring that everyone understands the meaning and use of data elements. Moreover, it provides documentation on changes to data elements and relationships over time, facilitating traceability and accountability. By ensuring that the data dictionary accurately reflects the structure and semantics of the database, we can maintain data quality and ensure that data is used consistently and correctly in all instances.
Ensuring the integrity and security of data within a database is crucial to maintaining data quality. Data integrity refers to the consistency and accuracy of data, while data security refers to the protection of data from unauthorized access, use, or modification. Data integrity can be ensured by using various techniques such as data validation, referential integrity, and auditing. Data security can be ensured by using access controls, encryption, and authentication. By ensuring data integrity and security, we can maintain data quality and protect sensitive information from misuse or theft.
Data warehousing is a critical concept in decision support. A data warehouse is a large, centralized repository of data from multiple sources that are used for analysis and reporting. A data warehouse provides a consolidated view of data, enables data mining and analysis, and facilitates decision-making by providing access to historical and current data. Data warehousing is applicable in decision support because it provides a reliable and accurate source of information on which to base decisions.
Healthcare data sets and standards used in healthcare data collection are critical for ensuring consistent, accurate, and reliable data. These data sets and standards define the data elements, codes, and formats used in healthcare data collection, ensuring that data is consistent and relevant across healthcare providers and stakeholders. Examples of healthcare data sets and standards include the International Classification of Diseases (ICD), the Current Procedural Terminology (CPT), and the Healthcare Common Procedure Coding System (HCPCS). By using these data sets and standards, healthcare providers can ensure that data is consistent and accurate, thereby improving healthcare quality and safety.
In conclusion, this assignment has explored the importance of database design, data dictionary, data integrity and security, data warehousing, and healthcare data sets and standards in maintaining high-quality data. By understanding these concepts, we can ensure that data is accurate, complete, consistent, valid, secure, and reliable. Moreover, by comparing and selecting the best databases for a particular application, we can optimize the use of data to support decision-making and improve healthcare outcomes.