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Schema: bob.balances Table: ez_balances_erc20_daily Type: Base Table

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What

This table provides daily ERC20 token balance snapshots for verified token contracts by making direct balanceOf contract calls at the end of each day. It captures the current token balance for each address-token pair that has had transfer activity, providing a comprehensive view of token holdings across all verified ERC20 tokens with decimal adjustments and USD valuations where available. Historical ERC20 balances data available, starting from 2025-06-10.

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Key Use Cases

  • Daily portfolio tracking and balance monitoring for ERC20 tokens
  • Historical balance analysis and trend identification
  • Token holder distribution analysis at daily granularity
  • Wallet balance snapshots for reporting and analytics
  • Cross-token balance comparisons and concentration analysis
  • Token supply distribution monitoring over time
  • Daily balance-based yield and return calculations

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Important Relationships

  • Join with fact_blocks: Use block_number for block metadata and timestamps
  • Join with dim_labels: Use address for entity identification and categorization
  • Join with dim_contracts: Use contract_address for token contract details
  • Join with ez_prices_hourly: USD valuations already included but can be refreshed
  • Join with ez_balances_native_daily: Compare with native token daily balances
  • Join with ez_token_transfers: Compare daily balances with transfer activity

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Commonly-used Fields

  • address: The account address holding the token balance
  • contract_address: The ERC20 token contract address
  • symbol: Token symbol (USDC, WETH, etc.)
  • balance: Token balance at end of day, decimal adjusted to standard units
  • balance_usd: USD value of the token balance at end of day
  • balance_raw: Raw balance in smallest token unit (wei equivalent)
  • balance_precise: Precise decimal-adjusted balance as string
  • decimals: Number of decimal places for the token
  • block_date: The date for which this balance snapshot was taken

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Sample queries

Daily Token Holdings by Address 
SELECT
    block_date,
    address,
    symbol,
    balance,
    balance_usd,
    contract_address
FROM <blockchain_name>.balances.ez_balances_erc20_daily
WHERE address = LOWER('0x1234567890123456789012345678901234567890')
    AND block_date >= CURRENT_DATE - 30
    AND balance > 0
ORDER BY block_date DESC, balance_usd DESC;
Token Holder Count Trends 
SELECT
    block_date,
    symbol,
    contract_address,
    COUNT(DISTINCT address) AS holder_count,
    SUM(balance) AS total_supply_tracked,
    AVG(balance) AS avg_balance,
    MEDIAN(balance) AS median_balance
FROM <blockchain_name>.balances.ez_balances_erc20_daily
WHERE block_date >= CURRENT_DATE - 90
    AND balance > 0
    AND symbol IS NOT NULL
GROUP BY 1, 2, 3
ORDER BY 1 DESC, holder_count DESC;
Portfolio Value Evolution 
-- Track portfolio value changes over time for specific addresses
SELECT
    block_date,
    address,
    COUNT(DISTINCT contract_address) AS token_count,
    SUM(balance_usd) AS total_portfolio_usd,
    STRING_AGG(
        CASE WHEN balance_usd > 100
        THEN symbol || ': $' || ROUND(balance_usd, 2)
        END, ', '
    ) AS major_holdings
FROM <blockchain_name>.balances.ez_balances_erc20_daily
WHERE address IN (
    SELECT DISTINCT address
    FROM <blockchain_name>.balances.ez_balances_erc20_daily
    WHERE balance_usd > 10000
    LIMIT 100
)
    AND block_date >= CURRENT_DATE - 30
    AND balance > 0
GROUP BY 1, 2
HAVING total_portfolio_usd > 1000
ORDER BY 1 DESC, total_portfolio_usd DESC;
Token Distribution Analysis 
-- Analyze token concentration and distribution patterns
SELECT
    symbol,
    contract_address,
    block_date,
    COUNT(DISTINCT address) AS total_holders,
    COUNT(DISTINCT CASE WHEN balance >= 1000 THEN address END) AS holders_1k_plus,
    COUNT(DISTINCT CASE WHEN balance >= 10000 THEN address END) AS holders_10k_plus,
    MAX(balance) AS max_balance,
    PERCENTILE_CONT(0.95) WITHIN GROUP (ORDER BY balance) AS p95_balance,
    PERCENTILE_CONT(0.50) WITHIN GROUP (ORDER BY balance) AS median_balance
FROM <blockchain_name>.balances.ez_balances_erc20_daily
WHERE block_date = CURRENT_DATE - 1
    AND balance > 0
    AND symbol IS NOT NULL
GROUP BY 1, 2, 3
HAVING total_holders >= 100
ORDER BY total_holders DESC
LIMIT 50;
Daily Balance Changes 
-- Compare daily balances to identify significant changes
WITH daily_changes AS (
    SELECT
        address,
        contract_address,
        symbol,
        block_date,
        balance,
        balance_usd,
        LAG(balance) OVER (
            PARTITION BY address, contract_address
            ORDER BY block_date
        ) AS prev_balance,
        LAG(balance_usd) OVER (
            PARTITION BY address, contract_address
            ORDER BY block_date
        ) AS prev_balance_usd
    FROM <blockchain_name>.balances.ez_balances_erc20_daily
    WHERE block_date >= CURRENT_DATE - 7
        AND balance > 0
)
SELECT
    block_date,
    address,
    symbol,
    balance,
    prev_balance,
    balance - prev_balance AS balance_change,
    balance_usd - prev_balance_usd AS balance_change_usd,
    CASE
        WHEN prev_balance > 0
        THEN ((balance - prev_balance) / prev_balance) * 100
        ELSE NULL
    END AS pct_change
FROM daily_changes
WHERE ABS(balance_change_usd) > 1000
    AND prev_balance IS NOT NULL
ORDER BY ABS(balance_change_usd) DESC
LIMIT 100;

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Columns

Column NameData TypeDescription
BLOCK_NUMBERNUMBERSequential counter representing the position of a block in the blockchain since genesis (block 0).
Key Facts:
  • Immutable once finalized
  • Primary ordering mechanism for blockchain data
  • Increments by 1 for each new block
  • Used as a proxy for time in many analyses
Usage in Queries: 
-- Recent data
WHERE block_number >= (SELECT MAX(block_number) - 1000 FROM fact_blocks)

-- Historical analysis
WHERE block_number BETWEEN 15000000 AND 16000000

-- Join across tables
JOIN <blockchain_name>.core.fact_event_logs USING (block_number)
Important: Block numbers are chain-specific. Block 15000000 on Ethereum ≠ block 15000000 on Polygon. | | BLOCK_DATE | DATE | The date for which this balance snapshot represents the end-of-day token balance. Example: ‘2025-07-04’ | | ADDRESS | TEXT | The account address whose token balance is recorded in this daily snapshot. Example: ‘0x1234567890123456789012345678901234567890’ | | CONTRACT_ADDRESS | TEXT | The ERC20 token contract address for which the balance is recorded. Example: ‘0xa0b86a33e6eb88b4d81b15e4e60c8a5b776e3b7a’ | | DECIMALS | NUMBER | Number of decimal places for the token, used for proper decimal adjustment in balance calculations. Example: 6 | | SYMBOL | TEXT | The token symbol for the ERC20 token. Example: ‘USDC’ | | BALANCE_HEX | TEXT | Hexadecimal representation of the token balance as returned by the balanceOf contract call. Example: ‘0x3b9aca00’ | | BALANCE_RAW | NUMBER | Token balance in the smallest unit (wei equivalent) without decimal adjustment, as returned by the contract. Example: 1000000000 | | BALANCE_PRECISE | TEXT | Token balance with proper decimal adjustment, returned as a string to preserve precision. Example: ‘1000.000000’ | | BALANCE | FLOAT | Token balance with decimal adjustment converted to a float for easier mathematical operations. Example: 1000.0 | | BALANCE_USD | FLOAT | USD value of the token balance at the end of the day, calculated using hourly price data. Example: 1000.50 | | EZ_BALANCES_ERC20_DAILY_ID | TEXT | Primary key - unique identifier for each row ensuring data integrity. Format: Usually VARCHAR containing composite key generated using MD5 hash of the relevant columns. Example: MD5(block_number, tx_hash, trace_index) Usage:
  • Deduplication in incremental loads
  • Join operations for data quality checks
  • Troubleshooting specific records
Important: Implementation varies by table - check table-specific documentation. | | INSERTED_TIMESTAMP | TIMESTAMP_NTZ | UTC timestamp when the record was first added to the Flipside database. Format: TIMESTAMP_NTZ Use Cases:
  • Data freshness monitoring
  • Incremental processing markers
  • Debugging data pipeline issues
  • SLA tracking
Query Example: 
-- Check data latency
SELECT
    DATE_TRUNC('hour', block_timestamp) as block_hour,
    DATE_TRUNC('hour', inserted_timestamp) as insert_hour,
    AVG(TIMESTAMPDIFF('minute', block_timestamp, inserted_timestamp)) as avg_latency_minutes
FROM <blockchain_name>.core.fact_transactions
WHERE block_timestamp >= CURRENT_DATE - 1
GROUP BY 1, 2;
``` |
| MODIFIED_TIMESTAMP | TIMESTAMP_NTZ | UTC timestamp of the most recent update to this record.

**Format**: TIMESTAMP_NTZ

**Triggers for Updates**:
- Data corrections
- Enrichment additions
- Reprocessing for accuracy
- Schema migrations

**Monitoring Usage**:
```sql
-- Recently modified records
SELECT *
FROM <blockchain_name>.core.fact_transactions
WHERE modified_timestamp > inserted_timestamp
AND modified_timestamp >= CURRENT_DATE - 1;

-- Data quality tracking
SELECT
    DATE(modified_timestamp) as mod_date,
    COUNT(*) as records_updated,
    COUNT(DISTINCT block_number) as blocks_affected
FROM <blockchain_name>.core.fact_transactions
WHERE modified_timestamp > inserted_timestamp
GROUP BY 1
ORDER BY 1 DESC;
``` |