Interactive GA4 Ecommerce Insights with Tableau Dashboard

Interactive GA4 Ecommerce Insights with Tableau DashboardInteractive GA4 Ecommerce Insights with Tableau Dashboard

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Tetiana Vinnytska

• Apr 4

GA4 Ecommerce Analysis & Tableau Dashboard

In this project, I transformed raw Google Analytics 4 data into an interactive Tableau dashboard.

Key highlights:

Processed 1.7GB of data in BigQuery using SQL (UNNEST, CTE).

Visualized the full User Purchase Journey and conversion rates.

Analyzed performance by device, OS, and landing pages to identify growth opportunities.

Product Data Analytics Google Analytics Data Analysis Data Visualization Google BigQuery Tableau

Sayedani Shaikh

• Apr 4

Title: Lead Management Dashboard — Data Visualization.

Description: Designed a lead management dashboard to visualize and track key sales metrics including lead status, conversion rates, and session sources. Created a sample dataset and built the dashboard to demonstrate how businesses can monitor their pipeline and make data-driven decisions at a glance.

Tools used:Canva (design), Power BI / Tableau (data visualization experience).

Data Analysis Canva Design Canva Data Visualization

Imaad Mahmood

• Apr 4

Built a full YouTube analytics dashboard in Google Looker Studio using real channel data from Dark Psychology Archive.

The dashboard tracks 6 KPIs — Views (18,582), Watch Time (51.2 hrs), CTR (4.32%), Likes (1,302), Subscribers Gained (105), and Engagement Rate (10.31%). A monthly trend line reveals the growth curve peaking at 4,266 views in November. Content-type breakdown shows Shorts drive 71% of total views. Top performer: Hoovering at 1,232 views with 8.2% CTR.

Built to help content creators make data-driven decisions on what to post, when, and in what format — without exporting CSVs manually.

Data Analysis Data Science Data Visualization Google Sheets Python Looker Studio

Onyendu Vivian

• Apr 4

Answers are buried in dataset, appropriate digging is all necessary

Working on a sales analysis project right now, and this first insight already has me talking to myself I noticed Yes Shipping was pulling more revenue with fewer orders and when I traced it back, it wasn't random. Three products were quietly doing the heavy lifting: BF1551 (Ornaments) at 2.27% net revenue with just 4.06% of orders, BF1544 and BF1545 (Other category) converting at 1.40% and 1.49% net revenue on only 2.92% and 2.46% of orders respectively. Fewer customers, higher returns after shipping costs. So let me ask you this if your data showed you exactly which 3 products to double down on, would you actually do it? Because this business now has that answer sitting right in their pivot table.