项目介绍

AsifRashid01/SalesAnalysis_SQL_PowerBI 是一个托管在 GitHub 上的开源项目,主要使用 TSQL 编写,目前获得 220 个 Star、34 次 Fork。

仓库全名
AsifRashid01/SalesAnalysis_SQL_PowerBI
Star 数
220
Fork 数
34

README 摘要

SalesAnalysisSQLPowerBI Setup This project requires SQL Server (SQL Express), Power BI Desktop We will work with backup Data Warehouse (DW) data and Lightweight (LT) data. Obtain data and restore following instructions from here. 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…

完整内容见 GitHub 原始 README 或本页 。

常见问题

SalesAnalysis_SQL_PowerBI 用什么语言开发?

主要使用 TSQL 编写,目前有 220 个 Star。

如何获取 SalesAnalysis_SQL_PowerBI 的源码?

可以直接克隆仓库:git clone https://github.com/AsifRashid01/SalesAnalysis_SQL_PowerBI.git,默认分支为 main;安装与运行步骤见仓库 README。

SalesAnalysis_SQL_PowerBI 最近还在维护吗?

仓库最近一次更新为 2021年9月11日,当前没有未关闭的 Issue;Star 数为 220,可作为社区活跃度的参考。

关于

Data Analyst portfolio project that deals with business KPIs, cleaning and transforming data and visualizing it to create a dashboard. The tools used are: SQL Server, T-SQL, Excel and Power BI.

描述取自 GitHub 官方 API,中文内容由 GitRead 中文社区 编辑团队整理。

简要分析

热度分
292
价值分
142
活跃状态
活跃

语言占比

TSQL

贡献者

README

SalesAnalysis_SQL_PowerBI

Setup

  • This project requires SQL Server (SQL Express), Power BI Desktop
  • We will work with backup Data Warehouse (DW) data and Lightweight (LT) data. Obtain data and restore following instructions from here.
  • 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.

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

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