Research / applied visualization
Using interactive data visualization for DeFi market analysis
An automated multi-source ETL workflow and interactive analytical interface for examining DeFi market structure and movement.
Reported full ETL
45 s
The paper also reports an 8-second incremental execution path.
Reported coverage
6,000+
protocols processed through the DeFiLlama source path.
Source APIs
3
CoinGecko, DeFiLlama and DexScreener.
Research question
Can an automated data pipeline and coordinated visual views reduce the friction of examining DeFi market structure and short-term movement?
The paper combines market and protocol data from three APIs, validates and transforms it into analytical outputs, and presents the result through synchronized Tableau views.
System view
From source data to analytical views.
01 Source APIs
Market & protocol data
CoinGecko
DeFiLlama
DexScreener
02 Data processing
Validate
Completeness, consistency, timeliness and outliers.
Transform
Normalize timestamps, derive features and aggregate.
03 Analytical delivery
Coordinated views
Overview, time series, movers and categories.
Four connected analytical outputsThe figure follows the system described in the paper: three source APIs pass through explicit validation and transformation boundaries before analytical delivery.
Method
- Collect token, protocol and exchange-pair data through three API clients with retry and backoff handling.
- Validate completeness, consistency, timeliness and outliers before transformation.
- Normalize timestamps, derive rolling features and aggregate market categories.
- Publish four analytical outputs for coordinated overview, time-series, movers and category views.
Results
| Measurement | Reported value | Conditions stated in the paper |
|---|---|---|
| Full ETL execution | 45 s | Complete multi-source pipeline |
| Incremental execution | 8 s | Incremental update path |
| Initial dashboard load | 3.2 s ± 0.5 | n = 100 |
| Filter operation | 1.8 s ± 0.3 | Interactive dashboard |
| Peak memory | 256 MB | Reported pipeline run |
Full ETL execution
- Reported value
- 45 s
- Conditions stated in the paper
- Complete multi-source pipeline
Incremental execution
- Reported value
- 8 s
- Conditions stated in the paper
- Incremental update path
Initial dashboard load
- Reported value
- 3.2 s ± 0.5
- Conditions stated in the paper
- n = 100
Filter operation
- Reported value
- 1.8 s ± 0.3
- Conditions stated in the paper
- Interactive dashboard
Peak memory
- Reported value
- 256 MB
- Conditions stated in the paper
- Reported pipeline run
These are measurements reported in the publication. A public reproducibility package is not currently linked here, so the portfolio does not present them as independently revalidated benchmarks.
Limits
- The paper notes that rehypothecation can inflate TVL measurements by 20–30%.
- Source APIs may lag by 5–15 minutes during high-volatility periods.
- The reported coverage excludes protocols below $1M TVL.
- User-efficiency and use-case claims remain paper-reported until their underlying evaluation artifacts are made public.
Other research
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