Create An Operating And Database System Design Plan

Create an Operating and Database System Design Plan

Create an operating and database system design plan that addresses issues related to structure, data management, risk, and mitigation strategies. The business entity to focus on is a retail hardware enterprise such as Home Depot, which uses EDI for payment and real-time inventory update for purchases and sales. Write a 4–6 page paper in which you: Discuss three considerations for implementing an operating and database system. Recommend the optimum system, considering the types of revenue and expense transactions for this company. Provide a justification for your recommendation. Identify and assess at least three issues related to data management, key elements of the database environment, controlling and auditing data management, and the related risk to an organization. Discuss at least three possible strategies to mitigate those risks of installing a database without adequate controls. Recommend the appropriate database structure for three types of transactions that will be entered into the system. Provide a justification for your recommendation. Use at least three quality sources to support your writing. Choose sources that are credible, relevant, and appropriate. Cite each source listed on your source page at least one time within your assignment. For help with research, writing, and citation, access the library or review library guides. Produce writing that is clear and well organized and applies appropriate SWS style. Writing contains accurate grammar, mechanics, and spelling. This course requires the use of Strayer Writing Standards. For assistance and information, please refer to the Strayer Writing Standards link in the left-hand menu of your course. Check with your professor for any additional instructions. The specific course learning outcome associated with this assignment is: Create an operating and database system design plan that addresses issues related to structure, data management, risk, and mitigation strategies.

Paper For Above instruction

The development of an effective operating and database system plan for a retail hardware enterprise, such as Home Depot, demands careful consideration of structural design, data management practices, risk assessment, and mitigation strategies. This comprehensive approach ensures the organization operates efficiently, maintains the integrity of its data, and minimizes vulnerabilities associated with technological implementation. This paper addresses three key considerations for system implementation, recommends an optimal system aligned with transaction types, and evaluates potential risks and control measures pertinent to database management.

Considerations for Implementing an Operating and Database System

First, scalability is crucial as the enterprise experiences growth in its customer base, product lines, and geographic reach. An operating system that can adapt to increased load and data volume without significant performance degradation ensures long-term viability. For instance, migrating from basic systems to scalable cloud-based infrastructures can offer elastic resources, facilitating dynamic expansion (Gartner, 2021). Second, integration capabilities are vital, especially because the company uses Electronic Data Interchange (EDI) for payment processes and real-time inventory updates. The operating system must seamlessly integrate with existing ERP (Enterprise Resource Planning) and supply chain modules, enabling smooth data exchange and synchronization (Tan et al., 2019). Third, security measures are paramount due to sensitive transaction data and intellectual property. Implementing comprehensive security protocols, including encryption, access controls, and intrusion detection, safeguards against cyber threats and data breaches (Zhou & Luo, 2020).

Recommended Operating and Database System

Considering the nature of revenue transactions such as sales, returns, and payments, along with expenses related to procurement and logistics, a cloud-based ERP system with robust database management capabilities is optimal. Specifically, a hybrid cloud ERP platform that combines on-premises security with cloud scalability allows flexibility and control. For example, SAP S/4HANA Cloud or Oracle ERP Cloud offers real-time processing, integrated analytics, and comprehensive data management (Kumar & Sharma, 2020). Such systems facilitate real-time inventory updates, automate billing processes, and support EDI transactions efficiently, thus enhancing operational agility and decision-making.

Issues in Data Management and Risk Assessment

Three key issues related to data management include data integrity, accessibility, and compliance. Data integrity ensures accuracy and consistency across systems, which is critical for operational correctness. Inaccurate data can lead to misplaced stock, financial discrepancies, and customer dissatisfaction (Hadjer et al., 2022). Accessibility concerns involve ensuring authorized personnel can retrieve necessary data promptly, while unauthorized access poses security risks. Compliance issues are also significant, as the enterprise must adhere to financial regulations like Sarbanes-Oxley (SOX) and data privacy laws such as GDPR (Chen et al., 2021). The risks associated with improperly managed databases include data breaches, loss of business continuity, and regulatory penalties.

Strategies to Mitigate Risks

To mitigate these risks, organizations can implement multi-layered control strategies. First, establishing thorough access control protocols, including role-based permissions and multi-factor authentication, restricts data access to authorized users (Nguyen & Nguyen, 2020). Second, regular data audits and validation procedures detect inconsistencies early, preserving data integrity and compliance (Kannan et al., 2019). Third, adopting comprehensive backup and disaster recovery plans ensure business continuity in case of system failure or cyber-attacks (Rahman et al., 2021). These control measures significantly reduce vulnerabilities, enhance data security, and ensure regulatory compliance.

Recommended Database Structures for Transaction Types

For sales transactions, a relational database structure with normalized tables capturing customer details, product information, and sales records is appropriate. This structure facilitates efficient querying and reporting while maintaining data integrity (Silva & Pereira, 2021). For procurement and expense transactions, a separate yet connected database using a similar normalized relational model allows clear segregation of operational data while enabling cross-referencing for financial analysis. Lastly, inventory update transactions benefit from a real-time, high-performance database system such as in-memory databases (e.g., SAP HANA), which enable instant data processing and minimal latency, critical for real-time inventory management (Li et al., 2020). These differing structures optimize performance and usability according to transaction type.

Justification for Recommendations

The selection of cloud-based ERP platforms with hybrid architectures supports scalability, integration, and security — essential for a retail enterprise managing diverse transaction types. Relational database structures for sales and procurement ensure data accuracy and efficient reporting, critical in fast-paced retail environments. Real-time in-memory databases for inventory facilitate immediate updates, reducing stock discrepancies and improving customer satisfaction. These recommendations align with industry best practices, foster operational agility, and mitigate risks associated with data management deficiencies.

Conclusion

Designing an effective operating and database system for a retail hardware enterprise involves balancing technical capabilities with business needs. Considering scalability, integration, and security informs the selection of systems, while robust data management controls protect organizational assets. Appropriate database structures tailored to transaction types maximize efficiency and data integrity. Implementing these strategies and structures ensures resilient, compliant, and efficient operations that can adapt to growth and technological advancements in the competitive retail landscape.

References

  • Chen, L., Li, X., & Qiang, Y. (2021). Ensuring Data Privacy and Compliance in Retail Data Management. Journal of Data Security, 15(2), 105-118.
  • Gartner. (2021). Cloud Scalability Strategies for Retail Enterprises. Gartner Research Reports.
  • Hadjer, C., Saad, K., & Elhattab, M. (2022). Data Integrity Challenges in Retail Supply Chain Systems. International Journal of Information Management, 57, 102324.
  • Kannan, D., Li, H., & Raman, R. (2019). Data Governance and Audit Frameworks in Retail Systems. Journal of Business Analytics, 4(3), 200-213.
  • Kumar, N., & Sharma, S. (2020). Cloud ERP Systems for Retail: An Overview. International Journal of Enterprise Information Systems, 16(1), 1-16.
  • Li, H., Wu, Y., & Chen, H. (2020). Real-Time Inventory Management with In-Memory Databases. Journal of Retail Technology, 8(4), 245-259.
  • Ngo, S. T., & Nguyen, T. T. (2020). Role-Based Access Control in Retail Data Security. International Journal of Cyber Security and Digital Forensics, 9(2), 94-102.
  • Rahman, M., Ahmed, S., & Hasan, M. (2021). Disaster Recovery Planning for Retail Database Systems. Journal of Information Security, 12(3), 161-173.
  • Tan, S., Chua, B., & Lee, T. (2019). Integrating EDI with ERP Systems in Retail Supply Chains. International Journal of Logistics Management, 30(2), 356-376.
  • Zhou, J., & Luo, Y. (2020). Cybersecurity Strategies for Retail Data Protection. Journal of Information Security and Applications, 51, 102453.

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