Miroslav Kopac

Project Overview

New Pizza Store is running takeout and delivery business. The owner requires to design and build relational database that allow him to capture and store all of important information and data that the business generates. This will help him to monitor business performance in dashboards

This report responds to the client's needs:

1. Customer orders information
2. When it’s time to order new stock
3. Which staff members are working when
4. The staff salary information

I took the following steps to create my analysis:

1. Designed and built a mock-up
2. Collected and normalized data
3. Defined table relationships and created a relational database using this website

Relational database

4. Created all queries using SQL (View SQL Queries on my Github)

To create orders dashboard, I need to query all necessary information from the order, item, and address tables, which are connected via IDs.

5. Visualized dashboards in Looker Studio using CSVs from queries

Developed an inventory optimization system based on real-time order patterns and stock levels, ensuring timely reordering and eliminating the risk of stockouts for the client

Created a staff management system to see who is working and to keep track of their salaries.

Project Overview

This HR Dashboard project uses synthetic employee data generated with ChatGPT prompts and the Python Faker library to simulate realistic HR metrics for analysis and visualization in Tableau.

Here are the points I was interested in answering:

1. How has employee hiring and termination trended over the years?
2. What is the current distribution of employees by department, job title, and location?
3. What does the workforce demographic look like in terms of gender, age, and education?
4. Is there a relationship between education level and employee performance?
5. How do salaries vary by age, gender, education, and department?

I took the following steps to create my analysis:

1. Generated realistic HR data using Python's Faker library + ChatGPT
2. Used Draw.io to plan visualization layout and user experience and Figma to enhance visualization
3. Created 9 different chart types for diverse data storytelling
4. Designed intuitive data visualizations in Tableau
5. Developed both executive summary views and detailed employee analysis

• Check and try dashboard here

Here are my key takeaways:

1. 20% of all terminations in the last 10 years occurred in 2020 —what might have driven this spike?
2. 70% of employees are based in HQ, with similar departmental distribution.
3. Gender balance is healthy; age distribution is normal and aligns with company culture.
4. 61% hold bachelor’s degrees, but high school grads show equal performance at lower cost—worth hiring more.
5. IT shows the most balanced salaries, while in Sales, women with PhDs earn 14K more than men despite no significant difference in performance—this warrants a closer review.

Project Overview

The purpose of sales dashboard is to present an overview of the sales metrics and trends in order to analyze year-over-year sales performance and understand sales trends.
The customer dashboard aims to provide an overview of customer data, trends and behaviors. It will help marketing teams and management to understand customer segments and improve customer satisfaction.

Here are the points I was interested in answering:

1. Total sales, profits and quantity for the current year and the previous year
2. Identifying months with highest and lowest sales
3. Comparing sales performance by different product subcategories
4. Weekly sales and profit data identifying weeks that are above and below the average
5. What is the distribution of customers based on the number of orders they have placed to provide insights into customer behavior, loyalty and engagement
6. The top 10 customers who have generated the highest profits

I took the following steps to create my analysis:

STEP 1 – Analyzed Requirements

STEP 2 – Built Data Source

STEP 3 – Built Charts

• Check and try dashboard here

STEP 4 – Built Dashboard

Here are my key takeaways:

1. Sales consistently grow through Q2–Q4 but drop sharply in Q1 each year, likely due to seasonal slowdowns and lack of targeted promotions. Launching year-end campaigns and loyalty incentives could help sustain momentum.2. Tables have not generated any profit over the past four years, consistently operating at a loss. Selling them as part of bundled sets with chairs or repositioning them in marketing could help turn this category around.3. Copiers are the most profitable subcategory. They should be prioritized in marketing and bundled with service plans to maximize revenue.4. The introduction of subscriptions led to more repeat customers and larger orders. Expanding subscription options and creating tiered benefits can further improve loyalty and revenue.