Harnessing Information Management, Data, And Infrastr 379295

Harnessing Information Management, the Data, and Infrastructure

In Assignment 1, you investigated data analytics and the utilization of data analytics in business. In this assignment, use the company or industry that you selected in Assignment 1. Use the Internet to explore the relationship between information management and data storage techniques. Write a four to six (4-6) page paper in which you:

Ascertain the importance of information management for the company or industry that you have chosen. Analyze the fundamental impact of IT architecture or enterprise architecture on information management for your chosen company or industry.

Determine if IT architecture impacts the effectiveness or efficiency of information management and vice versa. Suggest at least two (2) data storage methods regarding database, data warehouse, and/or data mart for your chosen company or industry. Provide a rationale for your response. Determine the optimal data storage method between the methods that you suggested in Question 3. Provide a rationale for your response.

Use at least three (3) quality references. Note: Wikipedia and other Websites do not qualify as academic resources. Your assignment must follow these formatting requirements: Be typed, double spaced, using Times New Roman font (size 12), with one-inch margins on all sides; citations and references must follow APA or school-specific format. Check with your professor for any additional instructions. Include a cover page containing the title of the assignment, the student’s name, the professor’s name, the course title, and the date.

The cover page and the reference page are not included in the required assignment page length. The specific course learning outcomes associated with this assignment are: Compare and contrast the strategic and operational use of data management systems. Summarize the complexities of information technology and practices. Use technology and information resources to research issues in information systems and technology. Write clearly and concisely about topics related to information systems for decision making using proper writing mechanics and technical style conventions.

Grading for this assignment will be based on answer quality, logic / organization of the paper, and language and writing skills. Click here to access the rubric for this assignment.

Paper For Above instruction

In today's data-driven business environment, effective information management is vital for organizations across industries. For the purpose of this paper, I have selected the healthcare industry to analyze the importance of robust information management systems, and how IT architecture influences data storage and overall efficiency.

The healthcare industry generates massive volumes of sensitive data, including patient records, billing information, clinical data, and operational metrics. Managing this information effectively is crucial for ensuring high-quality patient care, regulatory compliance, and operational efficiency. According to Raghupathi and Raghupathi (2014), effective health information management enhances decision making, improves patient outcomes, and reduces errors. The criticality of accurate, accessible data in healthcare underscores the importance of a well-structured information management framework.

The impact of IT architecture—comprising hardware, software, networks, and data repositories—directly influences the efficiency of information management in healthcare. Enterprise architecture (EA), which aligns IT infrastructure with business goals, provides a blueprint for integrating disparate systems (Jeongy et al., 2019). For example, an integrated electronic health record (EHR) system exemplifies how enterprise architecture facilitates seamless data sharing among providers, thereby improving clinical workflows and patient safety. Conversely, a fragmented IT architecture leads to data siloes, redundancies, and difficulties in data retrieval, ultimately hampering decision-making processes.

The effectiveness of information management is intrinsically linked to the underlying IT architecture—if the architecture is flexible, scalable, and interoperable, then the organization can utilize data more efficiently. Conversely, poorly designed architecture can create bottlenecks, increase operational costs, and diminish data accuracy and timeliness (Broom, 2018). This bidirectional relationship underscores the need for organizations to continually evaluate and enhance their IT architecture to support evolving data management needs.

Regarding data storage techniques, two prominent options are relational databases and data warehouses. Relational databases are highly structured, suited for transactional data, and excel at maintaining data integrity and consistency (Coronel & Morris, 2015). Data warehouses, on the other hand, are designed for analytical processing and reporting, integrating data from multiple sources to support decision-making (Inmon, 2005). For healthcare organizations, relational databases are ideal for day-to-day operations such as patient records and billing, while data warehouses enable advanced analysis of clinical outcomes, operational efficiency, and population health management.

Between the two, the data warehouse is often considered the more optimal storage solution for strategic decision-making in healthcare. Its capacity to aggregate and analyze large datasets from diverse sources provides a comprehensive view that supports clinical and managerial decisions. Moreover, data warehouses support complex queries and trend analysis that are not feasible with transactional relational databases due to performance constraints. Thus, while relational databases are indispensable for operational data, data warehouses offer superior capabilities for strategic analytics.

In conclusion, effective information management in healthcare hinges on the integration of appropriate data storage techniques and a robust IT architecture that fosters interoperability and scalability. Both relational databases and data warehouses have roles to play—relational databases ensure operational efficiency, while data warehouses support strategic insights. An aligned and well-designed enterprise architecture enhances the effectiveness of these storage methods, ultimately leading to improved decision-making, better patient outcomes, and organizational efficiency.

References

• Broom, M. (2018). The Role of Enterprise Architecture in Healthcare. HIMSS Journal, 54(2), 43-50.
• Coronel, C., & Morris, S. (2015). Database Systems: Design, Implementation, & Management (11th ed.). Cengage Learning.
• Inmon, W. H. (2005). Building the Data Warehouse (4th ed.). Wiley.
• Jeongy, S., Gharavi, H., & Riahi, S. (2019). Aligning Enterprise Architecture with Business Strategies in Healthcare. Journal of Medical Systems, 43(11), 245.
• Raghupathi, W., & Raghupathi, V. (2014). Big Data Analytics in Healthcare: Promise and Potential. Healthcare, 2(4), 319-330.