Convert Alteryx workflows to GCP

Alteryx in. Google Cloud out.

Deterministic parsers read the estate and emit native Google Cloud code — not Designer workflows wrapped in a new scheduler.

Alteryx → MigryX parser → BigQuery + Dataform + Composer

Alteryx

Designer.yxmd / .yxmc

Server / Gallery.yxzp packages

Batch macrosIn-DB tools

R / Python toolsEmbedded runtimes

→

MigryX Parser

Deterministic parseAI optional

Row-level parityBefore cutover

SQLX emitDataform models

DAG emitComposer

→

Google Cloud

BigQuerySet-based SQL

DataformGoverned models

Cloud ComposerReplaces scheduler

Cloud FunctionsNon-SQL tools

IAM + CLSLeast privilege

Git reposReproducible packs

AI is an optional add-on, off by default — the conversion runs end to end without it, air-gapped if your estate requires it.

Multi-Row Formula to BigQuery window function

A Multi-Row Formula calculating running totals with row offsets — the tool that forces analysts to think in terms of row pointers instead of SQL.

-- Multi-Row Formula: Running_Balance
-- Input: DAILY_TRANSACTIONS (sorted by Date)
-- Row-1 expression for running balance
-- with conditional reset on month boundary

GroupBy:    [Account_ID]
Expression: [Running_Balance] =
  IF DateTimeDiff(
    [Row-1:Date], [Date], "month") != 0
  THEN [Amount]
  ELSE [Row-1:Running_Balance] + [Amount]
  ENDIF
Num Rows:   1

-- Multi-Row Formula → window function
SELECT
    account_id,
    date,
    amount,
    SUM(amount) OVER (
        PARTITION BY account_id,
                     FORMAT_DATE('%Y-%m', date)
        ORDER BY date
        ROWS BETWEEN UNBOUNDED PRECEDING
                 AND CURRENT ROW
    ) AS running_balance
FROM daily_transactions
ORDER BY account_id, date;

Row-1 offset becomes a window function with PARTITION BY for the month boundary reset. Row pointer logic becomes declarative SQL. Scales from thousands to billions of rows without memory constraints.

Every conversion validated to row-level parity

Data Matching compares Alteryx output against BigQuery output — row by row, column by column. Differences flagged with root-cause analysis before sign-off.