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Data & Analytics

Describe the data. Get the spreadsheet.

Tell ZeroTwo 'all enterprise customers who signed up this quarter with their usage metrics and contract values.' It writes the SQL, pulls from your databases, joins the results in its sandbox, and delivers a clean spreadsheet. Every query is visible. Match rates are reported.

Integrates with:

What changes

Before
With ZeroTwo
Request to delivery
Hours to days depending on analyst availability
Minutes, depending on dataset complexity
Repeat requests
Start from scratch ('can you rerun that with Q1 data?')
Saved as a template, rerun anytime with current data
Cross-source joins
CSV exports and VLOOKUP, losing rows from ID mismatches
ZeroTwo pulls from each database and joins in its sandbox with match rates reported
Traceability
A spreadsheet with numbers and no record of how they were derived
Metadata tab with every query, match rate, and execution log

Request to delivery

Before

Hours to days depending on analyst availability

With ZeroTwo

Minutes, depending on dataset complexity

Repeat requests

Before

Start from scratch ('can you rerun that with Q1 data?')

With ZeroTwo

Saved as a template, rerun anytime with current data

Cross-source joins

Before

CSV exports and VLOOKUP, losing rows from ID mismatches

With ZeroTwo

ZeroTwo pulls from each database and joins in its sandbox with match rates reported

Traceability

Before

A spreadsheet with numbers and no record of how they were derived

With ZeroTwo

Metadata tab with every query, match rate, and execution log

Every stakeholder needs 'just one quick data pull.' You have twelve in the queue.

Sales needs enterprise customers with usage data by 3 PM. Marketing wants churned accounts with their last campaign touch. The CEO needs revenue by cohort and geography for a board slide. Each request is quick in isolation. Together, they're your entire week. And every one requires joining data that lives in different databases with different ID formats and a mapping table nobody documented.

The urgent ones get done with CSV exports and VLOOKUP, losing rows where IDs don't match across systems. The non-urgent ones sit in a Jira backlog growing faster than you can clear it. The analysis you were actually hired for gets pushed to 'next sprint' indefinitely.

How ZeroTwo builds custom datasets

1

Maps the plain-language request to tables and join keys

Google

ZeroTwo resolves 'enterprise customers with usage and contract data' to specific tables across your databases and generates a query plan you can review before execution.

2

Pulls product usage metrics via Postgres

Neon

Login frequency, feature adoption, and last-active timestamps staged for joining. SQL visible in the log.

3

Pulls customer records and contract data via MySQL

PlanetScale

ZeroTwo joins results from both databases in its sandbox. Match rate reported so you see how many records linked and which didn't.

4

Writes the clean spreadsheet with metadata

Google Sheets

ZeroTwo delivers named columns, summary statistics, and a metadata tab documenting every query, execution time, and row counts at each join stage.

On demand, or scheduled · Clean spreadsheet delivered to Google Sheets

Get started in under 10 minutes

1

Connect your tools

One-click OAuth for each integration. No API keys, no engineering.

2

Describe what you need

Give me all enterprise accounts that signed up in Q4 with their monthly usage, contract value, and support ticket count. Export it as a Google Sheet with one row per account.

3

It runs on schedule

On demand, or set a schedule so the dataset refreshes itself and lands in your spreadsheet.

Frequently asked questions

Yes. ZeroTwo generates a query plan mapping your request to specific tables and columns. You can review the SQL, edit it, or approve as-is before execution. Every query and its results are logged.

ZeroTwo pulls results from each database separately, then joins them in its sandbox using whatever shared keys exist: external IDs, email addresses, or mapping tables you define. Match rates are reported so you know how many records linked and which didn't. This is not a single SQL query across engines.

Yes. Every request is saved as a reusable template. Rerun against current data anytime, or schedule recurring runs like 'refresh this customer list every Monday.'

Yes. Neon and Supabase (Postgres) and PlanetScale (MySQL) simultaneously. ZeroTwo handles SQL dialect differences automatically. Cross-database joins happen in the sandbox, not as a single query.

Yes. They describe what they need in plain language. ZeroTwo translates it to SQL, executes across your databases, and delivers a spreadsheet. The data team can review the generated queries if needed.

Related workflows

Stop doing the work your tools should do for you.

Set it up once. ZeroTwo runs it every time.