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https://github.com/kusmn/tableau-googletrends-canada-analytics

Visualizes Canada’s top Google search terms (2020–2024) using BigQuery and Tableau to explore regional and temporal trends.
https://github.com/kusmn/tableau-googletrends-canada-analytics

bigquery data-visualization tableau

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Visualizes Canada’s top Google search terms (2020–2024) using BigQuery and Tableau to explore regional and temporal trends.

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# 🇨🇦 Google Trends Dashboard: What Canadians Googled (2020–2024)

This project analyzes and visualizes the **top most Googled search terms in Canada** between 2020 and 2024 using the **Google Trends public dataset on BigQuery**. The results are visualized in Tableau through an interactive dashboard.

[View Dashboard on Tableau Public](https://public.tableau.com/app/profile/usman.khalid4491/viz/GoogleTrend-Canada2020-2024/Dashboard1)

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## 🔍 Objective

- Extract search interest data from Google's BigQuery public dataset.
- Identify top 10 most Googled terms by **province**, **month**, and **year**.

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## 🧰 Tools & Technologies

- **Google BigQuery** – SQL-based data extraction and aggregation
- **Google Trends Public Dataset** – `bigquery-public-data.google_trends.international_top_terms`
- **Tableau Public** – Interactive map and bar chart visualization
- **Data Source Region**: Canada only

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## 📦 Dataset & Query Steps

### Step 1: Create Main Table Partitioned by Week
Extract Canadian search data from the international top terms table.

### Step 2: Aggregate Top 10 Terms by Region, Year, and Month
Use `AVG(rank)` and `ROW_NUMBER()` to determine most relevant searches per region/month.

### Step 3: Clean Region Names for Tableau
Standardize province/territory names for Tableau geolocation compatibility.

Full SQL queries are included in the [`sql/queries.sql`](sql/queries.sql) file.

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## 📊 Dashboard Features (in Tableau)

- **Top 25 terms** overall (by avg. rank)
- **Province-level maps** showing regional trends
- **Filter controls** for year and month
- **Dynamic top 10 search terms** per province
- Exportable **PDF snapshot** for offline reports

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## ✅ Insights Uncovered

- Sports events, national holidays, and public disruptions are frequently top-ranked.
- Certain terms show **seasonal or local interest** patterns.
- Regional differences in search behavior reflect local culture and current events.

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## 📌 Author

**Usman Khalid**
Data Analyst | Visual Analytics | Data Storytelling
📧 ukajk@live.com