• Transform data
• Discuss the use of calculations in Microsoft Access
• Use conditional analysis
• Use subqueries
• Discuss domain aggregation

You’ve just started as a database administrator at Global Retail, a growing chain of retail stores. Your first assignment is to help analyze their sales and inventory data to improve business operations.

The Situation

Global Retail has provided you with several datasets:

• Customer purchase history
• Store inventory levels
• Employee sales records
• Supplier information

Your manager has given you five specific tasks to complete using Microsoft Access:

Task 1:

The marketing team has combined customer lists from all store locations, but there are obvious data quality issues. Looking at the data, you notice:

Task 2:

You need to analyze sales performance for each store. The data includes:

• Daily sales totals
• Number of transactions
• Items per transaction
• Sales representative ID

Task 3:

The regional managers want to analyze sales data for different time periods and product categories.

Task 4:

The executive team wants to identify:

• Stores performing above the company average
• Products that haven’t sold in the last 30 days
• Top-performing sales representatives

Task 5: Regional Performance Summary

Create a summary of regional performance using domain aggregation functions to find:

• Total sales by region
• Average transaction value
• Number of active customers
• Highest performing store

Database Administration

In this Apply It activity, you’ve learned several essential database administration skills through a real-world retail scenario:

• Data Quality Management: Using tools like the Find Duplicates Query Wizard helps maintain accurate customer records, which is crucial for business analytics and customer service.
• Performance Analysis: Calculating metrics like average transaction value and growth rates helps businesses track their progress and make data-driven decisions.
• Flexible Querying: Parameter queries allow users to analyze data dynamically by specifying conditions like date ranges and categories, making reports more versatile and useful.
• Complex Comparisons: Subqueries enable sophisticated analysis by allowing comparisons against aggregated values, like identifying above-average performing stores.
• Data Aggregation: Domain aggregation functions (SUM, AVG, COUNT, MAX) help create meaningful summaries of business performance across different regions and time periods.

Remember: Effective database administration combines technical skills with an understanding of business needs to provide meaningful insights for decision-making.