DataSpark: Illuminating Insights for Global Electronics

Retail Analytics in the Electronics Industry

Problem Statement:

As part of Global Electronics' data analytics team, you are tasked with conducting a comprehensive Exploratory Data Analysis (EDA) to uncover valuable insights from the company’s data. Your goal is to provide actionable recommendations that can enhance customer satisfaction, optimize operations, and drive overall business growth.

Global Electronics, a leading retailer of consumer electronics, has provided you with several datasets containing information about their customers, products, sales, stores, and currency exchange rates. The company seeks to leverage this data to better understand their business and identify areas for improvement.

Business Use Cases:

By analyzing Global Electronics' customer, product, sales, and store data, we aim to identify key insights that will enhance marketing strategies, optimize inventory management, and improve sales forecasting. This will help tailor marketing campaigns, develop better products, plan effective promotions, and decide on store expansions and optimizations. Additionally, understanding the impact of currency exchange rates on sales will allow for better international pricing strategies. Overall, these insights will help Global Electronics increase customer satisfaction and drive business growth.

🛠 Skills

Data Cleaning and Preprocessing, EDA,Python, Data Management using SQL, Power Bi

Approach

• Data Cleaning and Preparation

  • Check for missing values and handle them appropriately
  • Convert data types where necessary (e.g., dates, numerical values).
  • Merge datasets where necessary for analysis (e.g., linking sales data with product and customer data).

• Load Data

  • Insert the preprocessed data into an SQL database by creating relevant tables for each data source and using SQL INSERT statements to load the data.

• Power BI Visualization

  • Connect SQL to Power BI/Tableau, import the data, and create interactive dashboards.

• Develop 10 SQL Queries

  • Formulate and execute 10 SQL queries to extract key insights from the data. These queries should address important business questions and support the analysis steps below.

Run Locally

Clone the project

  git clone https://github.com/Vijay6383/DataSpark-Illuminating-Insights-for-Global-Electronics.git

Go to the project directory

  cd DataSpark

Install dependencies

  pip install sqlalchemy

Demo

https://www.linkedin.com/posts/vijay-moses-avm_retailanalysis-powerbi-datadrivendecisions-activity-7226145944709316608-ktNN?utm_source=share&utm_medium=member_desktop

🔗 Links