Magnus Linden
Data Analyst
About Me
Naturally curious and observant. Thrives on new challenges and never stops seeking out learning opportunities and sharing knowledge.I enjoy solving problems with data, whether that is a personal problem, or on the job, using data to create better user experiences.
Skills
Power BI
SQL
Excel
Python
R
Git
Agile Development
Projects
Bellabeat Tracker Analysis (R)
The fitness tracker study analyzed smart device usage trends, revealing opportunities to target lower activity users with gradual progress features and optimize notification timing to align with daily activity patterns. Recommendations focused on promoting consistent activity and positioning Bellabeat devices as essential tools for improving health and wellness.
Bike Store Analysis (Power BI)
A comprehensive Power BI report that analyzes a diverse dataset including product details, sales history, and customer information, leading to optimized operations and improved customer satisfaction. By calculating key metrics and exploring critical business questions, such as product performance and spending trends, strategic decisions were made to boost sales and reduce returns.
LEGO Analysis (Python)
A detailed analysis using Pandas to explore trends in LEGO sets released from 1970 to 2022. Employed Matplotlib and Seaborn for data visualization, creating insightful charts like line graphs and scatter plots with regression lines to analyze the price-to-piece relationship. Additionally, statistical tests were conducted to assess the significance of differences observed, particularly regarding minifigures in licensed sets.
Budget Tracker (Excel)
The Budget Tracker is an Excel-based tool designed for comprehensive personal finance management, aimed at tracking and analyzing monthly income and expenses to provide a clear overview of financial health. It includes features for monitoring cash balance, setting daily budgets, establishing savings goals with target dates, and tracking progress towards these goals. Additionally, it offers insights into the percentage of monthly income saved, calculates the monthly savings needed to meet goals, and maintains a detailed transaction history sortable by various time frames for a complete financial overview.
Grocery Store Analysis (Power BI)
The Grocery Store Analysis encompasses two years of data (1997-1998) from a fictitious small grocery store chain, offering insights into store characteristics, sales, products, and customer profiles. Despite its compact size, the dataset provides detailed information, including store locations, sales transactions, product discounts, and customer demographics. Analysis focuses on calculating revenue and quantity sold by various metrics, customer demographics, and profit insights using Power BI's AI capabilities, addressing key questions about revenue, store count, customer segmentation, and profitability across different dimensions.
Pantry Manager (Python, Flask, SQL, HTML)
The Pantry Manager is a Flask-based CRUD web application designed for managing pantry inventories, leveraging a PostgreSQL database to persistently save and retrieve data. It enables users to display all current pantry items on the home page, add new items through a submission form, update existing item details, and delete items directly from the database, ensuring an up-to-date inventory management system.
For more projects, check out my GitHub here.