In this episode, we’re continuing our data analyst portfolio project by extracting and cleaning marketing data with SQL. This step in our data analyst project involves walking through various SQL transformations applied to each dataset table, preparing our data for visualization in Power BI.
We'll detail each SQL query, breaking down the transformations and explaining their purpose to ensure you have a clear understanding of each step. These skills are essential for any data analyst looking to build a comprehensive data analyst portfolio.
If you missed our introductory episode where we set up the project and explored the business case, I highly recommend watching it first—the link is in the description below. This will give you the foundational knowledge needed to follow along with this data analyst project.
Now, let's dive into the SQL details and start cleaning our marketing data!
Timestamps:
00:00 - Intro
00:46 - Product Table
07:00 - Customer Table
13:55 - Customer Review Table
16:28 - Engagement Table
19:05 - Customer Journey Table
29:24 - Next Episode
Resources and Downloads:
Data Analyst Portfolio Practice Environment Setup: • Data Analyst Portfolio Project - Envi...
Database & SQL Statements: https://github.com/aliahmad-1987/Data... (Resources starting with "Episode 2" in their name).
Series Overview:
Data Analyst Project - Solving a Business Problem - Power BI, SQL & Python
Data Analyst Project - Cleaning Data with SQL for Insights - Power BI, SQL & Python - • Data Analyst Project - Cleaning Data ...
Data Analyst Project - Advanced Sentiment Analysis with Python - Power BI, SQL & Python - • Data Analyst Project - Advanced Senti...
Data Analyst Project - Building an Interactive Dashboard in Power BI - Power BI, SQL & Python - Ep 4 - • Data Analyst Project - Building an In...
Data Analyst Project - Presenting Data For Stakeholders | Power BI, SQL & Python - • Data Analyst Project - Presenting Dat...
📩 Let’s stay in touch:
LinkedIn – / aliahmad1987