Alternative Data Labby Agile Layer
Case Studies

Proof, from the fragmented to the finished

A representative project showing how we take a hard, multi-source data problem and turn it into a dataset a research team can rely on.

Case Study03 / 08

DAO Governance + Historical Market Dataset

We built a research-ready dataset for 400+ DAOs by mapping DAO names to token tickers, extracting historical market data, reconciling missing tokens, testing multiple financial APIs, normalizing prices across USD/BTC/ETH, removing duplicates, and using manual chart extraction where APIs failed.

project readoutdelivered
DAOs processed400+
Data sources tested10+
Price historyHistorical coverage
NormalizationUSD / BTC / ETH
WorkflowAPI + manual extraction
DeliveryCSV / Excel, research-ready
Inside the build

The workflow behind the dataset

Every step existed to protect one thing: the trustworthiness of the final numbers.

01

Entity mapping

Mapped 400+ DAO names to their token tickers and contract addresses using fuzzy matching, then reviewed edge cases by hand to eliminate mismatches.

02

Source testing

Tested 10+ financial and crypto data APIs for coverage, history depth, and reliability — then selected the best source per token rather than trusting a single vendor.

03

Manual reconstruction

Where APIs had gaps or no coverage at all, we reconstructed historical prices directly from charts and dashboards, and reconciled them against known reference points.

04

Normalization

Normalized all pricing across USD, BTC, and ETH denominations so tokens could be compared on a consistent basis across the full time range.

05

Cleaning & dedup

Removed duplicates, resolved conflicting values between sources, standardized the schema, and flagged partial coverage explicitly instead of hiding it.

06

Delivery

Shipped a research-ready dataset in CSV and Excel, with documentation covering sources, coverage per token, normalization method, and known limitations.

Dataset Preview

What research-ready
actually looks like.

A sample of delivered structure — normalized, deduplicated, validated. Full datasets are scoped to your specific research question.

dao_market_dataset.csv
DAO NameTokenSourceDate RangePriceVolumeStatus
UniswapUNICoinGecko2020–Presentcompletecompleteprocessed
CompoundCOMPCoinMarketCap2020–Presentcompletecompleteprocessed
AaveAAVECoinGecko2020–Presentcompletecompleteprocessed
Nouns DAONOUNSCustom Extraction2021–Presentpartialavailableprocessed
MakerDAOMKRMulti-source2017–Presentcompletecompleteprocessed

// this is a sample preview. full datasets are built or delivered based on client requirements.

CSV / Excel delivery
API-ready structure
Postgres-ready schema
Documentation included
Validation notes included
08 / 08 — get started

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