Analyze your Quickbooks data in Python
Getting your data from Quickbooks to Python can be a pain. Managing pipelines for all your data sources just isn’t sustainable, but your reporting can’t be put on hold while you wait for IT or Engineering to get to your ticket.
With Panoply, you can eliminate that hassle—and all that wasted time. Set up code-free connections to both Quickbooks and Python with just a few clicks. Then Panoply will automatically sync your data so it’s ready to analyze when you are.
It’s that simple: Unblock your data with Panoply.
How it works
Automatically sync and store the data you want with table-level control.
See the Quickbooks data Panoply collects
Query-ready data with just a few clicks
Code-free data pipeline
Fuel your analytics
Integrate with Quickbooks in minutes
From P&L to profits, QuickBooks is a font of useful data for anyone trying to better understand their business. That can be a problem for finance and accounting departments that need to maintain control over who can log in to QuickBooks but don’t have time to continually pull ad hoc reporting for other teams.
That’s where Panoply comes in. Panoply is a combined ETL pipeline and data warehouse that’s built with usability in mind. Setup takes minutes, and when it’s done, you’re able to sync and store the QuickBooks data you choose in a secure data warehouse and connect it to your team’s favorite analytics and BI tools. The result? All the access you could want without the worry of someone accidentally breaking your bookkeeping.
Learn more:
Quickbooks Data Warehousing
Quickbooks Business Intelligence
Other connectors with Quickbooks
Integrate with Python in minutes
Love the power of Python for analytics and machine learning but need a way to support it alongside other BI tools? Panoply makes it easy to pipe data to multiple analytics tools with 30+ code-free connectors you can set up in minutes.
Along with eliminating API configuration and maintenance, Panoply automatically stores a copy of your data in the cloud, making your queries faster and more stable. Plus, by powering all your BI and analytics tools with the same centralized data you can ensure that key metrics are consistent across the company, no matter who’s doing the reporting.
Learn more:
Documentation
Other connectors with Python
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