Connector Database / Square
Analyze your Square data with AI
Build interactive dashboards, generate automated reports, and unlock business intelligence insights from your Square data with AI-powered assistant.
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Start with a question
Generate automated reports and business intelligence insights from your Square data—as fast as you can ask them.
Build dashboards and data visualizations
Transform your conversation into dynamic data visualizations on an intuitive data canvas.
Integrate all your data
Unify your Square data with DuckDB-powered data warehouse including MySQL, Google Sheets and PostgreSQL.
Available Square Data
Extracts Square commerce and financial data including locations, product catalog items and variations, orders with line items and tenders, refunds, vendors, payouts, and inventory counts. Enables revenue and order analysis, product performance tracking, stock monitoring, and payout reconciliation across Square locations.
Location
Represents each Square business location with capabilities and timezone; enables multi-location sales benchmarking, inventory allocation analysis, and payout reconciliation by site.
Product
Represents the product catalog including items, variations, and categories; supports product performance analysis, assortment optimization, and category/variant-level profitability tracking.
Inventory
Tracks on-hand counts of item variations by location; enables stockout detection, days of supply, replenishment planning, and inventory valuation across stores and SKUs.
Order
Represents customer orders with line items, tenders, totals, and state; used for revenue reporting, average order value, basket composition, and performance by product and location.
Refund
Represents payment and order-level refunds with amounts and status; supports returns rate analysis, net revenue calculation, and post-purchase adjustment reporting.
Vendor
Represents suppliers with status and profile details; enables vendor performance monitoring, purchase-side analytics, and supply risk tracking.
Payout
Represents settlements to bank accounts or other destinations with amounts, arrival dates, and status; supports cash flow forecasting and reconciliation from sales to deposits.
Authentication Required
Uses a Square access token (Bearer). If client ID, client secret, and refresh token are provided, it can refresh tokens via OAuth2 automatically.
Getting started with
Square Analytics & Business Intelligence
Connect your Square data
Connect to Square once and automatically sync data to your centralized data warehouse for real-time reporting and analytics.
Build business intelligence models
Create automated reports, dashboards, and data visualizations with customizable business logic and AI-powered insights for consistent analytics across your organization.
Generate reports and insights
Create interactive dashboards, automated reports, and data visualizations with AI-powered business intelligence. Share live analytics and scheduled reporting with your team.
Want to see how easy it is to get started?
Square usersDefinite
People love Definite because it lets you focus on what matters. Setting up your own data infrastructure doesn't make your beer taste better. Skip the tedium and start at analytics.
I was leading the efforts of setting up a business intelligence function. I was surprised how complex this all was to do even today. It's something that every tech company would need at some point but it hasn't been simplified. You need a whole team focused on building a data warehouse, setting up the right pipelines, and then integrating a BI tool on top.Definite wasn't only the answer to this problem, it tackled the next problem I knew I'd have as soon as the BI tool was ready — how do we get non-technical teams and people to learn and utilise such a tool.
Our analytics before Definite consisted of dozens of Excel sheets that took hours to update. Manual updates led to errors. Everyone questioned the accuracy of the numbers. Many people just stopped looking at the reports.After Definite, everything ran like clockwork.We immediately saved thousands of dollars per month in the time spent updating reports and have built strategies (e.g. improved ROI on ad spend, inventory management, etc.) on the data that will yield millions to our bottom line.
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