Super_Store_Sales_Analysis_Power_BI.pptx

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1. Super Store Sales Analysis and Visualization Using Power BI

2. Problem Statement Analyze the sales data of a Super Store to uncover insights and trends that can help improve business decisions and strategies.

3. Project Description Objective: The project focuses on performing Exploratory Data Analysis (EDA) on the Super Store sales data using Power BI. The primary objective is to extract meaningful insights and visualize the data to identify trends, patterns, and anomalies that can help improve business decisions and strategies. Dataset: Sample Super Store dataset including features like order date, ship date, customer details, product details, sales, profit, and region. Approach: 1. Data Collection: The dataset is sourced from a sample Super Store dataset, including various features such as order date, ship date, ship mode, customer details, product details, sales, profit, and region. 2. Data Preprocessing: Load the dataset into Power BI. Handle missing values and remove unnecessary columns. Convert data types if necessary to ensure consistency and accuracy. 3. Exploratory Data Analysis (EDA): Descriptive Statistics: Display summary statistics and understand the data structure. Unique Value Analysis: Identify unique values for categorical features. 4. Data Visualization: Bar Graphs: Visualize the distribution of categorical features. Pie Charts: Show the proportion of categories in specific columns. Histograms: Display the distribution of numerical features. Boxplots: Identify outliers in numerical features.

4. End Users Business Analysts: To understand sales performance and make data-driven decisions. Marketing Teams: To identify target segments and strategize marketing campaigns. Sales Teams: To focus on high-performing products and regions. Management: To get a high-level overview of business performance and strategic direction.

5. Technology Used Power BI: For data analysis and visualization. Data Import and Transformation: Using Power Query in Power BI. Visualization Tools: Utilizing the variety of visualizations available in Power BI to create insightful and interactive dashboards.

6. Importance Helps in identifying high-performing products and categories. Analyzes sales trends over time. Understands regional and customer segment performance. Provides data-driven recommendations for business growth.