https://github.com/mdanwarulkarim/data_analysis_report

This Data Analyst portfolio project focuses on business KPIs by cleaning, transforming, and visualizing data to develop a dashboard. The tools utilized in this project include Excel, SQL Server, T-SQL, and Power BI.
https://github.com/mdanwarulkarim/data_analysis_report

excel power-bi sql sql-server

Last synced: 5 days ago
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This Data Analyst portfolio project focuses on business KPIs by cleaning, transforming, and visualizing data to develop a dashboard. The tools utilized in this project include Excel, SQL Server, T-SQL, and Power BI.

• Host: GitHub
• URL: https://github.com/mdanwarulkarim/data_analysis_report
• Owner: mdanwarulkarim
• Created: 2024-10-02T15:04:03.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2024-10-02T15:21:33.000Z (3 months ago)
• Last Synced: 2024-11-07T18:53:02.590Z (2 months ago)
• Topics: excel, power-bi, sql, sql-server
• Language: TSQL
• Homepage:
• Size: 3.83 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# SalesAnalysis_SQL_PowerBI

### Setup

- This project requires Excel, SQL Server , Power BI Desktop

- We will work with backup Data Warehouse (DW) data and Lightweight (LT) data. Obtain data and restore following instructions from [here.](https://docs.microsoft.com/en-us/sql/samples/adventureworks-install-configure?view=sql-server-ver15&tabs=ssms)

- Compare DW and LT data to understand the difference between structured and unstructured data. We will primarily be working with Data Warehouse data.

- Update Data Warehouse data using [sql script.](https://github.com/techtalkcorner/SampleDemoFiles/blob/master/Database/AdventureWorks/Update_AdventureWorksDW_Data.sql)

### Business Request & User Stories

- Read the sample business request, demand overview & filled-out user stories to understand the problem we are trying to solve with Data Analysis and what we consider as a solution.

### Clean the Data using T-SQL

- Understand the difference between FACT tables & Dimension tables.

- Identify which tables in the data are of interest with the help of the Business Request form.

- Choose which columns are of interest to export by preparing and transforming these columns in SQL using concepts such as: renaming columns, combining columns, commenting in SQL script, formatting of SQL statements, WHERE clause, ORDER BY, LEFT JOIN, CASE() function and ISNULL() function. 

### Create Dashboard in Power BI

- Load Data

- Organize & Prepare Tables

- Connect Tables for Data Model

- Import Fact_Budget

- Calculation Measures

- Dashboard Design

- Import Custom Visual

- Measure Table

- Pie Chart

- Line Chart

- Bar Charts

- Map Graph

- Top 10 Graphs

- Gradient Bar Chart Color

- Customer Details

- Pivot Table

### Dashboard

- [Download the report file](https://github.com/mdanwarulkarim/Data_Analysis_Report/blob/main/Sales%20Report.pdf) and open in Power BI Desktop for interactive viewing.

- [See a screenshot](https://github.com/mdanwarulkarim/Data_Analysis_Report/blob/main/A%20Sales%20report%20overview.png) of the Dashboard in pdf.