For solo analysts

Your spreadsheet logic. A real database. Same afternoon.

Upload the CSV exports you already work with — Shopify, Stripe, QuickBooks, whatever generates the files you live in. SNADLY builds the database, writes the queries, and you spot-check the numbers against your spreadsheet. If you can use INDEX(MATCH), you can read the SQL.

Try it free How it works

The problem

You are one person. The reporting has to come from somewhere.

Every Monday, you export CSVs from the tools your company uses. You join them with INDEX(MATCH), clean the data, format the report, and email it out. By Tuesday, someone asks a follow-up that requires a different join. You rebuild Wednesday morning. Thursday's question uses data you did not export. Real analysis never happens.

Setting up a data warehouse sounds like another full-time job. It should not be. SNADLY builds the database for you. You verify the output against the numbers you already trust. That is it.

Not a project. An afternoon.

Upload. Verify. Go.

1. Upload your CSV exports

Drop in the files you already generate — Shopify orders, Stripe payments, QuickBooks invoices. No database connections needed.

2. SNADLY builds the database

It cleans the data, maps the relationships, and generates all the queries. This takes minutes, not weeks.

3. Spot-check against your spreadsheet

Run your usual Monday numbers. Do they match? If they do — and they should — you are done. If something looks off, you can inspect the query that produced it.

4. Answer questions from a query, not a rebuild

Next time the Head of Growth asks about customer segments from 6 months ago, you type a question instead of rebuilding a spreadsheet.

See the logic

Your INDEX(MATCH), as a query you can read.

You do not need to learn SQL before you start. But you can read what SNADLY writes. Every transformation is a plain text query — no black box, no mystery numbers. Below is the kind of thing SNADLY generates. If you can follow an INDEX(MATCH), you can follow this.

SELECT
  c.customer_name,
  c.email,
  COUNT(o.order_id) AS lifetime_orders,
  SUM(o.total)  AS lifetime_value
FROM customers c
JOIN orders o ON c.customer_id = o.customer_id
WHERE o.order_date > DATEADD('month', -12, CURRENT_DATE())
GROUP BY 1, 2
ORDER BY 4 DESC;

This is not a reporting cage. It is a real database you can query, connect to tools you might use later, or hand to someone else if the team grows. Nothing is locked into SNADLY.

What changes

Less rebuilding. More analysis.

One model of the business

Customers, orders, revenue, and products stop being separate CSV exports. They become tables that agree with each other.

Numbers you can trust

Spot-check the output against your existing spreadsheet. Same source data should give you the same numbers. If it does not, you can see exactly why.

Handles messy data

CSV exports, odd source fields, inconsistent IDs — that is what you work with. The pipeline expects it and cleans it.

Grows with you

Start with one CSV. Add more sources as the business asks for more reporting. You are not locking into a multi-year platform decision.

First step

Upload a CSV. Check your numbers.

Pick the export that takes the most time to rebuild every week. Upload it. SNADLY generates the database and queries. Spot-check the output against your spreadsheet. If the numbers reconcile, you have real infrastructure — not just another spreadsheet. If they do not, you lost an afternoon and nobody needs to know. No approvals, no proposals, no career risk.

Try it free