Kickstarter Campaign Analysis (SQL + BI Project)
Project: 1
Difficulty: Beginner
Tools: SQL Server, Power BI
Focus: Data Cleaning, Analysis, BI Reporting
This project focuses on analysing Kickstarter campaign data using SQL Server and Power BI to uncover patterns in project success, funding behaviour, and backer engagement.
The goal was to simulate a real-world analytics workflow by transforming raw data into structured insights that can support decision-making. The project demonstrates the full pipeline from data ingestion and cleaning in SQL to visualisation and reporting in Power BI.
- SQL Server Management Studio (SSMS)
- SQL (T-SQL)
- Power BI
- Excel / CSV (data source)
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Source: Kickstarter campaign dataset
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Data includes:
- Project goals
- Pledged amounts
- Backer counts
- Campaign outcomes (successful/failed)
- Categories and time trends
- Imported flat file data into SQL Server tables
- Defined appropriate data types for each column
- Validated schema and handled inconsistencies
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Checked for and handled NULL values
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Standardised formats across key fields
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Created derived metrics such as:
- Success indicators
- Aggregated pledged amounts
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Built structured datasets ready for analysis
Several analytical queries were developed to explore campaign performance:
- Analysed how campaign success rates change across time
- Identified patterns in successful vs failed campaigns
- Aggregated pledged amounts across campaigns
- Identified high-performing funding periods
- Examined how backer counts vary across campaigns
- Highlighted engagement patterns
- Investigated how funding goals impact campaign success
- Identified thresholds where success rates decline
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Connected SQL dataset to Power BI
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Built interactive dashboards including:
- KPI cards (total pledged, success rate)
- Bar charts (category performance)
- Trend analysis visuals
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Designed reports to communicate insights clearly
- Campaign success varies significantly depending on funding goals
- Moderate funding goals tend to have higher success rates
- Total pledged amounts are concentrated in a smaller number of campaigns
- High-performing campaigns significantly impact overall funding totals
- Campaigns with higher backer counts are more likely to succeed
- Engagement plays a critical role in campaign outcomes
- Extremely high funding goals correlate with lower success rates
- Indicates potential overestimation by campaign creators
- Presence of NULL values required validation and cleaning
- Some inconsistencies in formatting across fields
- Required multiple SQL transformations to prepare data for analysis
- Ensuring consistency across calculated fields was critical
- Designing meaningful visuals required careful selection of metrics
- Ensuring alignment between SQL outputs and Power BI visuals
- SQL data cleaning and transformation
- Writing analytical queries (aggregations, filtering, grouping)
- Data modelling for BI tools
- Dashboard development in Power BI
- Translating raw data into actionable insights
This project demonstrates the ability to take raw campaign data and transform it into meaningful insights using SQL and Power BI. It highlights key factors influencing Kickstarter success and showcases a complete end-to-end analytics workflow suitable for real-world business scenarios.
- Incorporate more granular time analysis (e.g. monthly trends)
- Apply advanced SQL techniques (window functions, CTEs)
- Enhance dashboards with additional interactivity and filtering
- Compare performance across different campaign categories