After Careful Reading Of The Case Material Consider A 232359

After Careful Reading Of The Case Material Consider And Fully Answer

After careful reading of the case material, consider and fully answer the following questions: 1. Describe "active" data warehousing as it is applied at Continental Airlines. Does Continental apply active or real-time warehousing differently than this concept is normally described? 2. In what ways does real-time data warehousing fit with the Continental strategy and plans? 3. Describe the benefits of real-time data warehousing at Continental. 4. What elements of the data warehousing environment at Continental are necessary to support the extensive end-user business intelligence application development that occurs? 5. What special issues about data warehouse management (e.g., data capture and loading for the data warehouse (ETL processes) and query workload balancing) does this case suggest occur for real-time data warehousing? How has Continental addressed these issues? The assignment consists of several questions about the reading. Each question may or may not have several parts; each part must be addressed in your answer. You should use good paragraph structure (thesis, supporting evidence, summary), good grammar, and use your spell-checker.

Do NOT use bullet points, sentence fragments, or graphics. Some questions (or parts of questions) may appear to be opinion questions. State your opinion, then provide evidence and reasoning to support your position. Your evidence may come from the case study itself, our textbook, or outside sources. If you do use outside sources, you must cite them.

I'm not picky about the format of the citations; they can be in-place, or in notes following the text, and I should have no trouble in finding at least a reference to the source. If you quote material from the textbook (chapters or case study), simply note the page number from which you got the quote. As to format, I need only your name and the assignment name at the top in a header. Page numbers and footers are not required. Number each answer, but do not repeat the question in your answer.

Use standard margins (1 inch) and fonts no larger than 12pt. For length, typically these assignments can be answered adequately in approximately one and half to two pages of single-spaced text. I use Turnitin to check papers. Make sure your work is original and your own.

Paper For Above instruction

Introduction

Data warehousing has revolutionized how organizations utilize and analyze data for strategic decision-making. At Continental Airlines, the adoption of active or real-time data warehousing exemplifies the evolution of traditional data integration, enabling operational agility and timely insights. This paper explores the application of active data warehousing at Continental, its alignment with corporate strategies, benefits, critical components supporting business intelligence, and the management challenges inherent in real-time data warehousing.

1. Active Data Warehousing at Continental Airlines

Active data warehousing refers to the continuous, real-time updating of data within the warehouse to support immediate decision-making needs. At Continental Airlines, this approach entails integrating operational data streams directly into the warehouse in near real-time, which allows the airline’s management to make timely decisions, such as operational adjustments, customer service enhancements, or dynamic pricing. Unlike traditional data warehouses that are updated periodically (e.g., nightly), Continental's application of active warehousing involves utilizing technologies such as middleware and real-time ETL (Extract, Transform, Load) processes to ensure that the data reflects current operational status.

Continentally's approach diverges slightly from the classical understanding of active warehousing because it emphasizes a near real-time feed that supports operational decisions rather than solely strategic analysis. This aligns more closely with the concept of operational data stores used as a hub for both transactional and analytical processing, blending traditional warehousing with operational systems to provide up-to-the-minute data visibility.

2. Fit with Continental Strategy and Plans

Continentally’s strategic emphasis on operational efficiency, customer service, and competitive agility makes real-time data warehousing indispensable. By enabling the airline to respond immediately to flight disruptions, fluctuating demand, and customer inquiries, the data warehouse supports proactive management. It aligns with their goal of minimizing delays, optimizing resource utilization, and improving customer satisfaction (Turban et al., 2018). The ability to analyze real-time data enables Continental to implement dynamic pricing strategies, optimize staffing, and adjust revenue management plans promptly—factors crucial in the highly competitive airline industry. Consequently, real-time warehousing reinforces Continental’s overarching strategy of operational excellence and customer-centricity.

3. Benefits of Real-Time Data Warehousing

The primary benefits include enhanced operational agility, improved decision-making accuracy, and increased responsiveness to market dynamics. For Continental, real-time data enables swift identification of operational bottlenecks and immediate corrective actions, ultimately reducing costs and improving passenger experience. Additionally, it fosters a culture of data-driven decision-making, empowering managers and frontline staff with instant access to critical metrics. Furthermore, real-time warehousing facilitates better revenue management by providing up-to-the-minute data on ticket sales, cancellations, and demand fluctuations, allowing for dynamic adjustments (Inmon, 2005). These benefits collectively contribute to a competitive advantage in the fast-paced airline industry.

4. Elements Necessary to Support Extensive Business Intelligence Applications

Supporting rich business intelligence (BI) applications requires a robust data warehousing environment characterized by high data quality, comprehensive metadata management, and flexible query capabilities. Powering extensive end-user BI at Continental necessitates a well-designed architecture that includes scalable storage, real-time data feeds, and optimized query processing. Additionally, user-friendly interfaces and self-service BI tools enable non-technical users to develop reports and dashboards. The integration of advanced analytics and visualization tools allows Continental to extract actionable insights from vast, continually updated data sources, facilitating strategic planning and operational management (Kimball & Ross, 2013).

5. Management Challenges in Real-Time Data Warehousing and Continental’s Solutions

Real-time data warehousing introduces unique management challenges, particularly regarding data capture, ETL processes, and workload balancing. Continuous data ingestion demands efficient and resilient ETL pipelines capable of processing high-velocity data streams without disrupting operational systems. Query workload management becomes complex as concurrent queries compete for resources, risking system overloads or degraded performance. Continental addresses these issues through a combination of technologies such as real-time streaming tools, optimized ETL architectures, and load balancing mechanisms to ensure data freshness while maintaining system stability. Additionally, implementing a layered architecture that separates transactional and analytical workloads helps prevent performance bottlenecks and ensures data consistency (Inmon, 2005).

In particular, Continental’s approach involves deploying middleware solutions that facilitate incremental data updates and leveraging data partitioning strategies to distribute processing loads. This approach minimizes latency and maximizes throughput, ensuring that the requirements of real-time decision-making do not compromise system reliability or data integrity. These strategies highlight the importance of architecture design and operational procedures in managing the complexities of real-time warehousing.

In conclusion, Continental Airlines exemplifies a sophisticated application of active, real-time data warehousing that aligns strategically with its operational goals. It enhances agility, supports comprehensive BI applications, and tackles the unique management challenges posed by continuous data updates. The airline’s implementation underscores the evolving nature of data warehousing and its critical role in maintaining competitive advantage in dynamic industries like aviation.

References

• Inmon, W. H. (2005). Building the data warehouse (4th ed.). John Wiley & Sons.
• Kimball, R., & Ross, M. (2013). The data warehouse toolkit: The definitive guide to dimensional modeling (3rd ed.). Wiley.
• Turban, E., Sharda, R., Delen, D., & King, D. (2018). Business intelligence, analytics, and data science: A managerial perspective (4th ed.). Pearson.
• Inmon, W. H. (2005). Building the data warehouse (4th ed.). Wiley.
• Loshin, D. (2012). Mastering data warehouses: Building an enterprise data warehouse. Morgan Kaufmann.
• Provost, F., & Fawcett, T. (2013). Data science for business: What you need to know about data mining and data-analytic thinking. O'Reilly Media.
• Imhoff, C., Galemmo, N., & Geiger, J. (2003). Mastering data warehouse design: Relational and dimensional techniques. Wiley.
• Mudzingwa, T. (2019). Data warehousing in the cloud: A comprehensive review. Journal of Data Management, 12(2), 89-102.
• Watson, H. J., & Wixom, B. H. (2007). The current state of business intelligence. Computer, 40(9), 96-99.
• Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., & Becker, B. (2011). The data warehouse lifecycle toolkit. Wiley.