Analyze your AppsFlyer data in Python
Getting your data from AppsFlyer 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 AppsFlyer 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 AppsFlyer data Panoply collects
Query-ready data with just a few clicks
Code-free data pipeline
Fuel your analytics
Integrate with AppsFlyer in minutes
AppsFlyer is a mobile app analytics SaaS tracks app behavior and mobile advertising data. Panoply comes with AppsFlyer integration, allowing companies to move their analytics directly into the Panoply Smart Data Warehouse without any ETL or ELT support needed.
Once within the data warehouse, Panoply allows you to connect and combine your AppsFlyer data with all of your other data sources and analytics. Your data is accessible in the cloud in minutes, and your marketing staff, data scientists, and data analysts can begin learning new ways to improve mobile conversions and generate revenue from within Panoply itself. Query, report, and follow your AppsFlyer data, all without the need to write custom scripts with Panoply.
Learn more:
AppsFlyer Data Warehousing
AppsFlyer Business Intelligence
Other connectors with AppsFlyer
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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