Consolidated Assignment - Sales Analysis and Performance Metrics

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These advanced, compound assignments are scenario-based and emulate real-world business challenges. They will require the use of various SQL functionalities, including but not limited to, joins, subqueries, CTEs, stored procedures, functions, and performance optimization techniques.

Here are some assignments, each combining various aspects of the tasks and assignments described above.

Sales Analysis and Performance Metrics

Context: As a Senior Data Engineer for a multinational online retail company, your team has been tasked with analyzing sales performance and customer behaviour. The analysis will help guide the company's growth strategy and identify potential markets for expansion.

The databases ClassicModels, HR, World, and Sakila are the primary data sources for this task.

Problem Statements - 1:

1. Using subqueries and joins, compile a comprehensive report showcasing sales trends across different regions in the world. The report should present the total sales for each product line in every country.
2. Using CTEs and window functions, identify the top-performing sales staff from the last year. Define performance based on the total sales they brought in, and identify any significant trends or patterns.
3. To optimize future sales strategies, identify the products that are frequently bought together. Use the concept of market basket analysis to find these product pairs or sets.
4. The HR team is planning an appraisal cycle. Help them by creating a stored procedure to calculate the average sales by an employee and identify the top 5% of employees based on this metric.
5. Query optimization is an integral part of your role. Review the queries you've written for this task, identify potential bottlenecks, and optimize them using appropriate techniques.

Sure, I can further elaborate and increase the complexity of the "Sales Analysis and Performance Metrics" assignment. Here's an expanded version:

Continuation

Context: As a Senior Data Engineer for a multinational online retail company, your team has been tasked with providing insights into the company's sales performance and customer behaviour for the last fiscal year. The primary data sources for this task are the ClassicModels, HR, World, and Sakila databases.

Problem Statements - 2:

1. Sales Trends Analysis: Write a multi-step SQL query using subqueries and JOINs to create a comprehensive report showcasing sales trends across different regions in the world. Include total sales and quantity sold for each product line in every country, the change in sales from the previous year, and the top 5 products by sales in each country. Provide these metrics on a quarterly basis for a more granular view of the sales trends.

2. Top-Performing Sales Staff: Use Common Table Expressions (CTEs) and window functions to identify the top-performing sales staff from the last year. Consider not only the total sales they brought in but also the number of new customers they acquired and the growth in sales from their accounts. Rank the sales staff based on these metrics to find the top performers.

3. Market Basket Analysis: To optimize future sales strategies, you've been asked to identify the products that are frequently bought together. Use SQL to perform a market basket analysis and find these product pairs or sets. Also, analyze how the frequently bought together items change across seasons and major sales events.

4. Sales Staff Performance Evaluation: The HR team is planning an appraisal cycle and requires your help. Create a stored procedure to calculate the average sales by an employee, the number of new clients they brought in, and the growth in sales from their accounts. Use this data to identify the top 5% of employees who have outperformed on all these metrics.

5. Optimization: As an integral part of your role, you need to ensure the queries run efficiently. Review the SQL queries written in the above tasks, identify potential bottlenecks, and optimize them using appropriate techniques like indexing, query reformulation, etc. Document the performance improvement achieved through each optimization technique applied.

6. Sales Forecasting: Write a SQL query to forecast next quarter's sales at a country level based on the historical sales data. Use a simple linear regression model for this prediction. Remember to transform your SQL output into a format suitable for linear regression.

Continuing from the previous assignment:

Context: As the Senior Data Engineer for a popular international movie streaming platform, your team is responsible for aiding in strategic decision-making. Using the ClassicModels, HR, World, and Sakila databases, you must analyze customer behavior to enable personalized marketing and increase customer retention.

Problem Statements:

1. Customer Segmentation: The marketing team wants to create personalized advertisements and offers for different segments of customers. Write a SQL query that segments customers into distinct groups based on rental history, preferred genres, total expenditure, and demographic data. Utilize window functions, subqueries, and JOIN operations to accomplish this.

2. Customer Retention Analysis: Analyze customer churn by determining the number of customers who stopped renting films each month over the last year. Identify any trends or patterns and suggest possible reasons based on associated customer data. This task will involve creating complex JOINs across multiple tables and aggregating the results to monthly level.

3. Popularity Trends: Find out the popularity trends of different genres and categories over the last year. Write a SQL query to find the number of rentals of movies in each category, by month for the past year. This will require a complex query involving multiple JOIN operations, grouping sets and date functions.

4. High Value Customers: Identify high-value customers who have rented the most number of movies and have the highest total expenditure. Include their demographic details and their most frequently rented film categories. This will involve multiple window functions, subqueries and JOIN operations.

5. Optimization: The database has started to perform slowly due to the complex operations. You need to ensure efficient query performance. Use indexes, partitioning, and other optimization techniques to improve query performance, and document the process and the achieved improvements.

6. Personalized Marketing Strategy: Write a stored procedure that takes in a customer ID and returns a list of suggested movies for that customer, based on their rental history and preferred genres. The marketing team can then use this list for personalized recommendations.

7. Customer Feedback Analysis: Analyze the feedback given by customers. Create SQL procedures to automatically categorize feedback into 'positive', 'negative', and 'neutral' based on keywords.

These assignments are designed to emulate real-world scenarios and challenges that a data engineer would encounter in a business setting. The complexity lies in understanding the business context, applying the appropriate SQL concepts, and optimizing for performance. The assignments encourage not only technical proficiency but also strategic thinking and problem-solving skills.