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This repository contains a Power BI solution for AtliQ hardware, enabling comprehensive analysis of sales trends, informed decision-making, and revenue growth in the brick and mortar business.

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shantamgarg24/Sales-Insights-Using-PowerBI-and-SQL

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Sales Insights Using PowerBI and SQL

Problem Statement:

AtliQ hardware, a brick and mortar business specializing in hardware goods, is facing challenges in understanding and analyzing its sales trend. The current lack of visibility into the sales data hinders the business's ability to make informed decisions and take proactive measures to drive growth. Without a comprehensive understanding of the sales trend, AtliQ hardware struggles to identify patterns, anticipate customer demand, optimize inventory, and tailor marketing strategies effectively. As a result, the business is unable to capitalize on potential growth opportunities and achieve its revenue goals. To overcome these obstacles, AtliQ hardware recognizes the need to implement a solution that provides a clear and insightful view of the sales trend, enabling data-driven decision-making and facilitating strategic actions to increase revenue and improve overall performance.

Solution Approach:

To address the problem statement, the following approach was used:

* Data Import and Initial Analysis:

The sales data was provided in a SQL dump file, which was imported into a SQL database. Initial insights were drawn from the data using SQL queries and analysis techniques to gain a preliminary understanding of the sales trend.

* Connecting SQL Database to Power BI:

The SQL database was connected to Power BI, establishing a live connection or importing the necessary data tables into Power BI.

* Data Modeling and Relationship Creation:

Data modeling was performed within Power BI to create relationships between the relevant tables in the SQL database. This step ensured that the data could be properly analyzed and visualized.

* Data Cleaning and Transformation:

Power BI's data transformation features, such as Power Query, were utilized to clean and transform the data. Irrelevant entries, duplicates, and inconsistencies were removed or resolved, ensuring the data was accurate and reliable.

* Dashboard Creation - Key Insights:

The first type of dashboard, "Key Insights," was created to provide an overview of the sales trend. This dashboard focused on presenting high-level metrics, such as total sales, top-selling products, sales by region, and sales by time period. Visualizations like charts, graphs, and KPIs were used to convey the key insights effectively.

* Dashboard Creation - Profit Analysis:

The second type of dashboard, "Profit Analysis," aimed to provide in-depth insights into the profitability of AtliQ hardware goods. This dashboard included visualizations and calculations related to profit margins, cost analysis, and product profitability. It allowed users to identify profitable products, assess cost effectiveness, and optimize pricing strategies.

* Dashboard Creation - Performance Insights:

The third type of dashboard, "Performance Insights," focused on analyzing the performance of AtliQ hardware goods. This dashboard provided visualizations and metrics related to sales performance, sales growth, customer segmentation, and market share. It enabled users to track performance trends, identify growth opportunities, and make data-driven decisions.

Each dashboard was designed to be interactive, allowing users to filter and drill down into specific dimensions or time periods of interest.

Expected Outcome:

By implementing the above solution approach, AtliQ hardware expects to achieve the following outcomes:

  • Enhanced Data Analysis: The connection between the SQL database and Power BI enables real-time or near-real-time analysis of the sales trend. The solution provides users with the ability to explore and analyze data more efficiently, leading to better insights and understanding.

  • Improved Decision Making: The creation of the three dashboards (Key Insights, Profit Analysis, and Performance Insights) equips users with a comprehensive view of the sales trend from different perspectives. This enables informed decision making, such as identifying profitable products, optimizing pricing strategies, and targeting specific customer segments.

  • Increased Efficiency: By utilizing Power BI's data transformation features, data cleaning and transformation tasks are streamlined. This saves time and effort, allowing users to focus more on analyzing the data and extracting valuable insights.

  • Revenue Growth: With the ability to access key insights, analyze profitability, and monitor performance effectively, AtliQ hardware anticipates achieving a revenue growth of at least 7% in the next quarter. The data-driven decision making facilitated by the Power BI dashboards contributes to identifying growth opportunities and implementing effective strategies.

Overall, this solution approach leverages the power of SQL and Power BI to provide a robust data analysis and visualization solution, empowering AtliQ hardware to make informed decisions and drive revenue growth.

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This repository contains a Power BI solution for AtliQ hardware, enabling comprehensive analysis of sales trends, informed decision-making, and revenue growth in the brick and mortar business.

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