Scanned By CamScanner Project 2 Milestone 3 DW Reporting

Scanned By Camscannerproject 2 Milestone 3 Dw Reporting And Visualiza

This milestone uses the implemented database that is the output of Milestone 2 to produce reports and visualizations implemented with SQL Rollup queries. This is the final step in Project 2 and provides a hands-on application of the concepts related to using a data warehouse for addressing users' questions. It involves writing the SQL queries needed to retrieve the data and thinking from a user/management perspective to determine the best visualizations for presenting this data.

The complete SQL needed to address management’s key objectives using the fact and dimension tables of the data warehouse are created along with a description of the results suitable for presentation to management. A detailed project report should be submitted on the due date. This project is to be done individually. This may require additional reading and research. To complete assignment, you should complete the following activities:

1) Review the management questions you developed carefully. 2) For each question identify the fact and dimension tables needed. 3) Complete the activities listed below under submission requirements.

Paper For Above instruction

The following academic paper addresses the key components of Milestone 3, focusing on the generation of SQL reports using rollup queries and creating visualizations to communicate data insights to management. It demonstrates the application of data warehouse concepts, SQL expertise, and visualization techniques to support managerial decision-making in a hotel and resort corporation context.

Introduction

Data warehouses (DWs) serve as central repositories that consolidate data from various operational databases, enabling complex analysis and reporting. Milestone 3 emphasizes transforming this data into actionable insights through SQL reporting and visualizations. This process entails understanding management questions, designing appropriate SQL queries—particularly using the ROLLUP and CUBE features—and crafting compelling visualizations to communicate findings effectively.

Methodology

The foundation of this project involves leveraging the data warehouse constructed in Milestone 2, which integrates data from two large hotel corporations. The initial step requires revisiting management questions—such as revenue trends, occupancy rates, and customer demographics—and determining the fact and dimension tables pertinent to each question. Subsequently, specific SQL queries utilizing ROLLUP and CUBE are crafted to aggregate data along multiple dimensions.

Three critical management questions are selected for reporting: revenue by region and time, guest satisfaction ratings per hotel and service type, and occupancy rates segmented by hotel and season. For each, corresponding fact and dimension tables are identified—for example, the FactRevenue table combined with dimension tables like HotelDim, RegionDim, and TimeDim. SQL commands are written to extract, summarize, and prepare data, often involving grouping and aggregation with ROLLUP or CUBE to produce comprehensive reports that encapsulate various hierarchical levels of data.

The visualization component involves exporting query results to tools like Excel or Tableau for creating intuitive graphics. Three distinct visualizations are developed: bar charts illustrating revenue trends over time, heat maps showing guest satisfaction across regions and hotels, and pie charts depicting occupancy rates by season. These visualizations aim to highlight patterns and facilitate strategic decisions at the managerial level.

Results and Discussion

The generated SQL queries effectively leverage rollup functionalities to produce multi-level summaries, enabling management to drill down or roll up data as needed. For example, a query aggregating revenue by region, hotel, and quarter reveals regional performance and hotel-specific trends. Sample results demonstrate clear hierarchical summaries, essential for understanding granular and aggregate performance metrics.

The visualizations, once created, provide accessible insights. The bar chart displaying revenue over quarterly periods aids in identifying peak seasons and underperforming locations. Heat maps of guest satisfaction scores facilitate pinpointing problem areas needing improvement. Pie charts of occupancy rates across seasons help in resource planning and marketing adjustments. These visualizations complement the SQL reports, making complex data more understandable for non-technical stakeholders.

Conclusion

Milestone 3 integrates SQL reporting and visualization techniques aligned with management questions, demonstrating the value of a well-designed data warehouse. The use of ROLLUP and CUBE functions streamlines the creation of multi-dimensional summaries, critical for comprehensive analysis. The resultant visualizations serve as effective communication tools, empowering management with insights to optimize operations, enhance guest satisfaction, and increase revenue.

Future work may include automating report generation, expanding visualizations to include trend analysis, and integrating real-time data feeds for dynamic reporting. This project underscores the importance of combining robust data warehousing, advanced SQL queries, and compelling visualizations to support strategic decision-making in hospitality management.

References

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