Harnessing Information Management, the Data, and Infrastructure ✓ Solved

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 or Strayer Library 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.

Paper For Above Instructions

Data analytics plays a critical role in modern businesses, helping them uncover insights that drive decision-making, optimize processes, and enhance customer engagement. For this assignment, I'll focus on American Express, a leading financial services company renowned for its innovative use of data analytics. This paper explores the importance of information management, the impact of IT architecture on data management, and evaluates various data storage methods suitable for American Express.

Importance of Information Management

Information management pertains to how organizations collect, store, and utilize data to make informed decisions. For American Express, effective information management is paramount. With vast amounts of data generated daily from transactions, customer interactions, and market trends, a structured approach to information management enables the company to enhance its service offerings, improve customer loyalty, and mitigate risks associated with fraud.

First, information management allows American Express to analyze consumer behavior effectively. By leveraging data analytics, the company can identify spending patterns and preferences, enabling more personalized marketing initiatives. For instance, targeted promotions and product recommendations can significantly enhance customer experience, leading to increased revenues and stronger customer relationships (Cameron, 2013).

Moreover, information management aids in risk assessment and fraud detection. American Express employs sophisticated algorithms to analyze transaction patterns in real-time, detecting anomalies that may indicate fraudulent activity. Thus, ensuring data integrity and security is essential, necessitating a robust information management strategy that adheres to privacy regulations while allowing for comprehensive data analysis (Marr, 2016).

Impact of IT Architecture on Information Management

IT architecture, which refers to the structural design of IT systems including hardware, software, networks, and data management, profoundly influences information management at American Express. An optimal IT architecture facilitates seamless data flow and interoperability between different systems, enhancing overall data management efficiency.

For example, American Express utilizes a cloud-based infrastructure that allows for scalable data processing capabilities necessary for handling large data volumes. This architecture not only supports current operational demands but also lays the foundation for future growth as data volumes continue to rise. Consequently, the choice of IT architecture significantly impacts the effectiveness of information management, forming the backbone that supports various analytics functions (Ghosh, 2017).

Furthermore, IT architecture can directly influence the efficiency of information management processes. When systems are poorly integrated or based on outdated technology, accessing and analyzing data can be cumbersome, leading to delays and decreased productivity. In contrast, a modern IT architecture that encourages data sharing and availability empowers teams to make faster, data-driven decisions.

Data Storage Methods

In terms of data storage, American Express can leverage several methods to optimize its data management strategy. Two effective data storage techniques include:

  • Data Warehouse: A data warehouse serves as a centralized repository of integrated data from multiple sources, optimized for querying and analysis. For American Express, implementing a data warehouse would facilitate comprehensive data analysis across various departments, driving more informed decision-making. It enables features like historical analysis, trend identification, and cross-departmental insights.

  • Database Management Systems (DBMS): DBMS are essential for managing structured data in real time. American Express can use relational databases to handle transactional data efficiently. Given the nature of its business, where quick access and processing of transactional information are crucial, a robust DBMS would ensure performance and reliability in data operations.

Optimal Data Storage Method

Choosing an optimal data storage method between a data warehouse and database management system depends on the specific needs and functions at American Express. While both options are valuable, a data warehouse might be the more suitable choice due to its capacity for extensive analytics and reporting across various data types. It allows American Express to derive actionable insights from historical and real-time data, fostering enhanced strategic planning and operational efficiency.

The rationale for the preference towards a data warehouse lies in the increasing emphasis on business analytics and actionable insights. As American Express continues to refine its marketing and customer service strategies, the ability to analyze comprehensive data sets holistically becomes paramount (Ingram Micro Advisor, 2015).

Conclusion

In conclusion, information management is critical to the operational success of American Express, shaping its approach to data analytics and customer relationship management. Through effective IT architecture, the company can streamline information management processes, enhancing efficiency and decision-making capabilities. The implementation of a data warehouse could provide American Express with significant advantages in terms of comprehensive data analysis, equipping the organization to navigate future challenges and capitalize on emerging market opportunities.

References

  • Bean, R. (2016, April 27). Inside American Express' big data journey. Retrieved from [link]

  • Cameron, N. (2013, April 11). How predictive analytics is tackling customer attrition at American Express - CMO Australia. Retrieved from [link]

  • Ghosh, A. (2017, August 12). Advantages & Disadvantages of Using IBM Big Data Analytics On Cloud. Retrieved from [link]

  • Ingram Micro Advisor. (2015, March 24). Four Types of Big Data Analytics and Examples of Their Use. Retrieved from [link]

  • Marr, B. (2016, January 13). American Express Charges into the World of Big Data. Retrieved from [link]

  • Rouse, M. (2016, December 30). What is data analytics (DA)? - Definition from WhatIs.com. Retrieved from [link]

  • Zgola, M. (2015, August 4). A Deep Dive into Data Analytics – Capella University. Retrieved from [link]