How to combine data from Google Analytics Multi-Channel Funnels Reporting API with IBM Informix

Pipes allows you to quickly Integrate Google Analytics Multi-Channel Funnels Reporting API with IBM Informix data for a combined analysis.
Load data from Google Analytics Multi-Channel Funnels Reporting API and IBM Informix into your central data warehouse to analyze it with the business intelligence tool of your choice.
Pipes allows you to connect to Google Analytics Multi-Channel Funnels Reporting API, IBM Informix, and more than 200 other APIs, web services, and databases with ready-to-use data connectors. Automate your data workflows through data pipelines without a single line of code.
1

Connect your data warehouse

It will be the destination of all data pipelines you build. Pipes supports relational databases in the cloud and on-premises.
2

Connect to Google Analytics Multi-Channel Funnels Reporting API and IBM Informix

You just need to enter the associated credentials to allow Pipes access to the Google Analytics Multi-Channel Funnels Reporting API API and the IBM Informix API.
3

Combine data from Google Analytics Multi-Channel Funnels Reporting API and IBM Informix

Pipes lets you select the data from Google Analytics Multi-Channel Funnels Reporting API and IBM Informix that you want to load to your data warehouse. These data pipelines will run automatically on your defined schedule!

About Google Analytics Multi-Channel Funnels Reporting API

Google’s Multi-Channel Funnels Reporting API enables you to request Multi-Channel Funnels data for an authenticated user. Data is derived from conversion path data, which shows user interactions with various traffic sources over multiple sessions prior to a conversion. It allows you to analyze how multiple channels influence conversions over time.

About IBM Informix

IBM Informix is a product family within IBM’s Information Management division that is centered on several relational database management system (RDBMS) offerings. The Informix server supports the object-relational model, which has permitted IBM to offer extensions that support data types that are not a part of the SQL standard. The most widely used of these are the time series and spatial extensions, which provide both data type support and language extensions that allow high performance domain specific queries and efficient storage for datasets based on time series and spatial data.

Your benefits with Pipes

Get central access to all your data

Access data from 200+ data sources with our ready-to-use connectors and replicate it to your central data warehouse.

Automate your data workflows

Stop manually extracting data and automate your data integration without any coding. We maintain all pipelines for you and cover all API changes!

Enable data-driven decision-making

Empower everyone in your company with consistent and standardized data, automate data delivery and measure KPIs across different systems.