Analyze your Facebook Posts data in Python
Getting your data from Facebook Posts 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 Facebook Posts 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 Facebook Posts data Panoply collects
Query-ready data with just a few clicks
Code-free data pipeline
Fuel your analytics
Integrate with Facebook Posts in minutes
Instantly integrate Facebook post data into the Panoply cloud data warehouse so that it is immediately available for analysis. Facebook allows businesses to download and export post data and insights, and the Panoply integrates that data into your existing warehouse without requiring any ETL process or management.
Once loaded, the data is available to be combined, connected, or otherwise analyzed with all of your other data sources - all from within the Panoply platform. With Panoply, you can enhance your understanding of post engagements, better know your audience, grow your page, and enhance the relevancy of your social media presence to potential consumers.
Learn more:
Documentation
Facebook Posts Data Warehousing
Facebook Posts Business Intelligence
Other connectors with Facebook Posts
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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