
Oracle JSON_TABLE for Turning Documents Into Rows Explained
How Oracle's JSON_TABLE projects a JSON document into relational rows and columns, with row paths, nested paths, ordinality, ON ERROR and ON EMPTY clauses.
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How Oracle's JSON_TABLE projects a JSON document into relational rows and columns, with row paths, nested paths, ordinality, ON ERROR and ON EMPTY clauses.

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Move a fragile Excel model into a SQL view: map inputs, calculations and outputs, translate formulas, run both in parallel and keep Excel as the front end.

Turn SQL Server rows into JSON with FOR JSON PATH and AUTO, nest child rows, control nulls and wrappers, and avoid the double-encoding trap with JSON_QUERY.

Reconcile two Excel reports with SQL: compare grand totals, then group totals, then rows with a full outer join, and sort the differences into causes.

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Turn an array of objects into CSV in JavaScript by hand or with csv-stringify: quoting, dates, booleans, formulas, BOM and a streaming writer.

The old Excel XML Spreadsheet 2003 format is plain XML with Worksheet, Row, Cell and Data elements. Read it with lxml, handle Index gaps and types.

Turn an Excel export of orders into a cohort retention table with SQL: first purchase month, months since, a retention triangle and honest recent cohorts.

How OPENJSON turns a JSON array or object into rows in SQL Server, with the default key, value and type columns, the WITH clause, nested arrays and the traps.

Load 2,000,000 CSV rows into PostgreSQL and SQLite from Node and compare per-row inserts, batches, transactions and COPY, with timings and failure behavior.

Build simple forecast baselines from monthly history in SQL: last value, seasonal naive, moving average and linear trend, and test them on held out months.