Ndubuisi Ononiwu

• • NDUBUISI IHEANYICHUKWU ONONIWU Nigeria --www.linkedin.com/in/ndubuisi-ononiwu-91bb9336 Hi I am a Data Analyst and also a Certified Business Analyst (CPBA). I'm a passionate Data Analyst with about 2 years of experience in transforming raw data into actionable insights that drive informed decision-making. My expertise lies in data cleaning, statistical analysis, and creating compelling visualizations that tell a story. I am committed to delivering high-quality results with an attention to detail and a focus on client needs. FINANCIAL ANALYSIS ON SUPERMARKET SALES Data Analyst Financial Analysis Project: Utilizing Power BI Ndubuisi Ononiwu Introduction Supermarket business landscape requires effective financial analysis for strategic decisionmaking and operational efficiency. This project presents a comprehensive financial analysis leveraging Power BI to visualize and analyze transactional data. The dataset includes various important variables: Invoice ID, Branch, Customer Type, Product Line, Unit Price, Quantity, Tax (5%), Total Price, Date, Time, Payment Method, COGS (Cost of Goods Sold), Gross Margin Percentage, Gross Income, and Customer Rating. The aim of this project is to derive insights into customer and city purchase trends, track Key Performance Indicators (KPIs), and provide actionable recommendations to enhance business performance. Objectives: 1. Sales Performance Analysis: We will evaluate the total sales by Product Line, Payment Type, Customer Type and Branch to identify the most profitable areas. 2. Customer Demographics: We will analyze customer data to understand the buying patterns and payment pattern of Customers in different Cities. 3. Product Performance: We will Identify the performance of Product Lines in all the Cities and Product Lines with Gender to guide inventory and marketing strategies. 4. Trend Analysis: We will examine Gender purchase trends in all the Cities to predict future sales performance. Problem Statement Supermarket businesses face challenges in understanding which Customer type, Product Line, Payment Method and Branch contribute most to their total revenue. This project aims to uncover valuable trends, insights and answer the following key questions such as: Which Customer type is driving sales? What are the best-selling Product Line? Which Branch contributes the most to the overall sales? Which Payment Method contribute the most to the overall sales? This project aims to systematically address these questions by conducting a detailed financial analysis of the available dataset, ultimately providing actionable insights to help optimize sales strategies, optimize inventory management, improve operational efficiency and help the organization make informed strategic decisions. Data Overview The following columns form the basis of this analysis: • Invoice ID: A unique identifier for each invoice. • Branch: The location of the sale (e.g. Branch A, Branch B). • City: The city where the branch is located (e.g. Naypyitaw, Yangon, Mandalay) • Customer Type: The classification of the customer (e.g. Member, Normal). • Product Line: Category under which the product falls. (e.g. Food & Beverages, Fashion Accessories, Electronic Accessories, Home & Lifestyle, Health & Beauty, Sports & Travel) • Unit Price: Price per unit of product sold. • Quantity: Number of units sold. • Tax (5%): Tax applied to the sale. • Total: Total sales amount paid by the customer. • Date: The date of the transaction. • Time: The time of the transaction. • Payment: Method used for the transaction (e.g., Cash, Credit Card). • COGS: Cost of Goods Sold for each transaction. • Gross Margin Percentage: Measures the percentage of revenue exceeding COGS. • Gross Income: Total revenue minus COGS. • Rating: Customer’s rating of the product/service. Key Performance Indicators (KPIs) To assess business performance effectively, we will focus on the following KPIs: • Total Revenue is 322.97k. • Total Units Sold is 5510. • Average Unit Price is 55.67 • Total Gross Income is 15.38k. • Average Rating is 6.97 • Total COGS is 307.59k • Total Tax Collected is 15.38k Recommendations 1. Customer Segmentation: We have two customer types (Normal & Member) using Content Marketing and Social Media Marketing will be effective in marketing our entire product line. 2. Sales Efficiency: The following products has high sales in the following cities: Food & Beverages & Electronics Accessories in Naypyitaw. Home& Lifestyle, Sports Accessories in Yangon. Health & Beauty & Fashion Accessories in Mandalay. We should focus on promoting and stocking such products in those cities. 3. Pricing Review: Pricing review should be done for such products that have low sales: Home and Lifestyle in Naypyitaw, Health & Beauty, Fashion Accessories in Yangon and Food & Beverage in Mandalay to maximize profit margins. 4. Inventory Management: The inventory levels should be optimal on products that have high sales: Food & Beverages & Electronics Accessories in Naypyitaw. Home& Lifestyle, Sports Accessories in Yangon. Health & Beauty & Fashion Accessories in Mandalay to optimize stocking strategies. Conclusions. This Financial analysis revealed the following based on customer transactions in the cities (Naypyitaw, Yangon, Mandalay): the females purchased more Fashion Accessories products and less of Health & Beauty products while the males purchased more Health & Beauty products and less of Fashion Accessories. The Total revenue for the cities were comparable: Naypyitaw is 110,568.71 (34.24%), Mandalay is 106,197.67 (32.88%), Yangon is 106,200.37 (32,80%) The KPIs calculated and visualized allow management to monitor performance, identify trends, and make data-driven decisions. Sales Analysis of Product Delivery by Train Services: Utilizing Python Data Analyst Ndubuisi Ononiwu Introduction: This project on Sales analysis of products delivered to various regions and cities using the train services, it will focus on analyzing a train dataset that contains critical information regarding sales transactions, shipping modes, customer details, product categories, and regional metrics. By analyzing this dataset, we aim to identify trends, assess performance across various segments, and uncover actionable insights that can enhance strategic decisions and improve customer satisfaction. The analysis will utilize various visualizations and metrics to derive meaningful conclusions from the dataset. Objectives: 1. Sales Performance Analysis: We will evaluate the total sales by region, segment, and product category to identify the most profitable areas. 2. Customer Demographics: We will analyze customer data to understand the buying patterns based on different demographics and regions. 3. Shipping Mode Efficiency: We will Investigate the efficiency of different shipping modes in relation to sales figures. 4. Product Performance: We will Identify 10 top-performing and underperforming products to guide inventory and marketing strategies. 5. Trend Analysis: We will examine sales trends over time to predict future sales performance. Problem Statement: Product manufacturing companies face challenges in understanding which segments, products, and shipping modes contribute most to their total revenue. This project aims to uncover valuable trends, insights and answer the following key questions such as: Which customer segments are driving sales? What are the best-selling products across regions? How does the choice of shipping mode influence overall sales? By addressing these questions, we can provide actionable insights to help optimize sales strategies and improve operational efficiency. Key Performance Indicators (KPIs): 1. Total Sales: The sum of sales across different categories is as follows: Technology is 820000, Furniture is 700000, & Office Supplies is-. Sales by Region: Sales performance segmented by geographical regions is as follows: West is 720000, East 680000, Central is 500000 & South is-. Sales Growth Rate: The percentage change in sales over time (if time-series data is available). 4. Top-selling Products: Canon Image CLASS 2200 Advanced Copier had the highest Total Sales of the Top 10 Selling Products being the product which generated the most revenue while High Speed Automatic Electric Letter Opener. 5. Customer Segmentation Analysis: The Consumer segment has 50.8% being the highest Overall sales while the Home office segment has 18.8% the lowest Overall sales. Analysis and Visualizations: 1. Sales Performance Analysis o . Analysis: The Total Sales for West Region was the highest being the high performing area while the total sales for South region was the lowest being the low performing area o Analysis: The Total Sales by Ship Mode the Standard Class was the highest being the high performing area while the total sales for Same Day was the lowest being the low performing area Analysis: The Total Sales by Category the Technology was the highest being the high performing area while the total sales for Office Supplies was the lowest being the low performing area 1. Customer Demographics: o Analysis: The Consumer segment has 50.8% being the highest Overall sales while the Home office segment has 18.8% the lowest Overall sales. 1. Shipping Mode Efficiency: o Analysis: The Standard Class has the highest average sales being the most profitable shipping mode while Same Day has the lowest average sales. 1. Product Performance: o Analysis: Canon Image CLASS 2200 Advanced Copier had the highest Total Sales of the Top 10 Selling Products being the product which generated the most revenue while High Speed Automatic Electric Letter Opener. 2. Trend Analysis: o Analysis: The Sales trends from the table below shows low sales at the beginning of the year while the sales peak towards the end of the year. Trend Analysis Table. Year- Month February September February October January November January November Rating Lowest Highest Lowest Highest Lowest Highest Lowest Highest Sales >10,000 80,000 15,000 75,000 17,000 95,000 20,000 115,000 Recommendation: We have drawn the following recommendations based on our analysis findings: o Targeted marketing strategies: We should enhance our marketing strategy for Home Office and Corporate so as to increase their market share. o Inventory management and stocking strategies: We should ensure optimal inventory and stocking management for Technology and Furniture and Office Supply towards the end of the year when their sales are at the peak based on our Trend Analysis o Potential new markets or focus areas: We should focus our market on The West and East where we had the highest geographical sales while also developing strategies to improve our market share on the Central and South regions Conclusion: This Sales Analysis of product delivery using the train services, we provided a comprehensive view of sales performance across various dimensions such as region, customer demographics, shipping modes efficiency, product performance and trend analysis. The insights gained from these visualizations and assessments will enable stakeholders to make informed strategic decisions, optimize operations, and ultimately drive business growth.